yap-users — General Information on Yap

[Yap-users] Logtalk 3.44.0 released

[Paulo M. <pm...@lo...>]

Hi,

Logtalk 3.44.0 is now available for downloading at:

https://logtalk.org/

This release features new and improved linter checks; adds a new Handbook nomenclature section on the differences between Logtalk and Prolog; adds new Handbook glossary entries; adds libraries for CSV files reading/writing, option handling, and term input/output from/to atoms, chars, and codes; improves existing libraries; provides fixes and improvements for several developer tools; adds a shell script for generating Allure reports from test results; adds support for exporting test result in the xUnit.net v2 XML format; improves exporting of results in the JUnit/xUnit format; includes new and improved programming examples; adds new examples to the ToyCHR port; adds tests sets for the de facto standard hyperbolic arithmetic functions; adds additional tests for several arithmetic functions; adds Windows installer experimental support for creating an integration shortcut for Tau Prolog; updates the macOS installer support for users of the zsh shell; removes support for Qu-Prolog and for the multi-threaded version of XSB; and includes portability updates for LVM, SICStus Prolog, SWI-Prolog, Tau Prolog, Trella ProLog, YAP. For details and a complete list of changes, please consult the release notes at:

https://github.com/LogtalkDotOrg/logtalk3/blob/master/RELEASE_NOTES.md

You can show your support for Logtalk continued development and success at GitHub by giving us a star and a symbolic sponsorship:

https://github.com/LogtalkDotOrg/logtalk3

Happy logtalking!
Paulo

-----------------------------------------------------------------
Paulo Moura
Logtalk developer

[Yap-users] Logtalk 3.43.0 released

[Paulo M. <pm...@lo...>]

Hi,

Logtalk 3.43.0 is now available for downloading at:

https://logtalk.org/

This release
focus once again on improved testing support and improved test suites for both Logtalk features and Prolog standards compliance of supported backends. It also provides compiler improvements and bug fixes, provides experimental support for Trealla ProLog; updates support for LVM and Tau Prolog; improves the top-level shortcut for loading files; includes a new "git" library; adds new predicates to the "queues" library; provides portability fixes for the "os" library; provides new predicates, improvements, and fixes for the "lgtunit" tool; provides fixes for the "debugger" and "lgtdoc" tools; improves the portability of the "bench" and "metainterpreters" examples; provides UltiSnips support for the Vim text editor, kindly contributed by Paul Brown; and includes other portability updates for most of the supported backends. For details and a complete list of changes, please consult the release
notes at:

https://github.com/LogtalkDotOrg/logtalk3/blob/master/RELEASE_NOTES.md

You can show your support for Logtalk continued development and success at GitHub by giving us a star and a symbolic sponsorship:

https://github.com/LogtalkDotOrg/logtalk3

Happy logtalking!
Paulo

-----------------------------------------------------------------
Paulo Moura
Logtalk developer

Re: [Yap-users] mmap error at Ubuntu 20.04

[Vitor S. C. <vs...@gm...>]

Stefan

I am trying to launch 7 but that is dragging on, so maybe it is a good
idea to fix 6.2.

Just to be on sync, give me a url with the version please

Thanks

Vitor

On Sun, Nov 1, 2020 at 8:42 PM stefanx <st...@lr...> wrote:
>
> Anybody here ?? Ubuntu 20.04 is not that unimportant.
>
>
> Am 28.10.20 um 20:41 schrieb stefanx:
> > "mount -o remount,exec /dev" seems to work, see
> >
> > https://bugzilla.redhat.com/show_bug.cgi?id=710802
> >
> > GRUB_CMDLINE_LINUX_DEFAULT="iomem=relaxed" doesn't work
> >
> >
> > Am 28.10.20 um 19:52 schrieb stefanx:
> >> yap...@li...,
> >>
> >> Yap 6.2.2 doesn't work at Ubuntu 20.04
> >>
> >> dpkg -i yap_6.2.2-6+b5_amd64.deb
> >> ...
> >>
> >>> yap
> >> %
> >> %
> >> % YAP OOOPS: mmap could not map at 0x10000000, got 0xffffffffffffffff.
> >> %
> >> %
> >>
> >>    Exiting ....
> >>
> >>
> >> See also
> >> https://stackoverflow.com/questions/61663746/yap-6-2-2prolog-mmap-error-during-compilation-on-ubuntu-20-04
> >> https://forum.ubuntu-it.org/viewtopic.php?t=640137
> >>
> >>
> >> Regards
> >>
> >> Stefan
> >>
> >
> >
> > _______________________________________________
> > Yap-users mailing list
> > Yap...@li...
> > https://lists.sourceforge.net/lists/listinfo/yap-users
>
>
>
> _______________________________________________
> Yap-users mailing list
> Yap...@li...
> https://lists.sourceforge.net/lists/listinfo/yap-users

Re: [Yap-users] mmap error at Ubuntu 20.04

[stefanx <st...@lr...>]

Anybody here ?? Ubuntu 20.04 is not that unimportant.

 
Am 28.10.20 um 20:41 schrieb stefanx:
> "mount -o remount,exec /dev" seems to work, see
>
> https://bugzilla.redhat.com/show_bug.cgi?id=710802
>
> GRUB_CMDLINE_LINUX_DEFAULT="iomem=relaxed" doesn't work
>
>
> Am 28.10.20 um 19:52 schrieb stefanx:
>> yap...@li...,
>>
>> Yap 6.2.2 doesn't work at Ubuntu 20.04
>>
>> dpkg -i yap_6.2.2-6+b5_amd64.deb
>> ...
>>
>>> yap
>> %
>> %
>> % YAP OOOPS: mmap could not map at 0x10000000, got 0xffffffffffffffff.
>> %
>> %
>>
>>    Exiting ....
>>
>>
>> See also
>> https://stackoverflow.com/questions/61663746/yap-6-2-2prolog-mmap-error-during-compilation-on-ubuntu-20-04
>> https://forum.ubuntu-it.org/viewtopic.php?t=640137
>>
>>
>> Regards
>>
>> Stefan
>>
>
>
> _______________________________________________
> Yap-users mailing list
> Yap...@li...
> https://lists.sourceforge.net/lists/listinfo/yap-users

Re: [Yap-users] mmap error at Ubuntu 20.04

[stefanx <st...@lr...>]

"mount -o remount,exec /dev" seems to work, see

https://bugzilla.redhat.com/show_bug.cgi?id=710802

GRUB_CMDLINE_LINUX_DEFAULT="iomem=relaxed" doesn't work


Am 28.10.20 um 19:52 schrieb stefanx:
> Hello,
>
> Yap 6.2.2 doesn't work at Ubuntu 20.04
>
> dpkg -i yap_6.2.2-6+b5_amd64.deb
> ...
>
>> yap
> %
> %
> % YAP OOOPS: mmap could not map at 0x10000000, got 0xffffffffffffffff.
> %
> %
>
>    Exiting ....
>
>
> See also
> https://stackoverflow.com/questions/61663746/yap-6-2-2prolog-mmap-error-during-compilation-on-ubuntu-20-04
> https://forum.ubuntu-it.org/viewtopic.php?t=640137
>
>
> Regards
>
> Stefan
>

[Yap-users] mmap error at Ubuntu 20.04

[stefanx <st...@lr...>]

Hello,

Yap 6.2.2 doesn't work at Ubuntu 20.04

dpkg -i yap_6.2.2-6+b5_amd64.deb
...

> yap
%
%
% YAP OOOPS: mmap could not map at 0x10000000, got 0xffffffffffffffff.
%
%

   Exiting ....


See also
https://stackoverflow.com/questions/61663746/yap-6-2-2prolog-mmap-error-during-compilation-on-ubuntu-20-04
https://forum.ubuntu-it.org/viewtopic.php?t=640137


Regards

Stefan

[Yap-users] Logtalk 3.38.0 released

[Paulo M. <pm...@lo...>]

Hi,

Logtalk 3.38.0 is now available for downloading at:

https://logtalk.org/

This release adds a new lint check for non-tail recursive predicate definitions, improves the lint checks for deprecated predicates, includes fixes and improvements for the "arbitrary" library category, implements several new QuickCheck options, simplifies error handling and reporting for the QuickCheck predicates and test dialects, improves the documentation of several developer tools, improves the usability of the SVG diagrams generated by the "diagrams" tool by adding CSS support, and updates support for the Kate text editor. For details and a complete list of changes, please consult the release notes at:

https://github.com/LogtalkDotOrg/logtalk3/blob/master/RELEASE_NOTES.md

You can show your support for Logtalk continued development and success at GitHub by giving us a star and a symbolic sponsorship:

https://github.com/LogtalkDotOrg/logtalk3

Happy logtalking!
Paulo

-----------------------------------------------------------------
Paulo Moura
Logtalk developer

[Yap-users] RW 2020 - Call for Applications for the 16th Reasoning Web Summer School

[<ma...@ma...>]

[apologies for multiple postings]


=================================================================

******************************************************
CALL FOR APPLICATIONS

The 16th Reasoning Web Summer School (RW 2020)
24-26 June, 2020
Virtual event (free registration)

https://2020.declarativeai.net/events/rw-summer-school

Part of "Declarative AI 2020: Rules, Reasoning, Decisions and Explanations"
(DeclarativeAI 2020, https://2020.declarativeai.net)
******************************************************

The purpose of the Reasoning Web Summer School is to disseminate recent
advances on reasoning techniques and related issues that are of particular
interest to Semantic Web and Linked Data applications. It is primarily
intended
for postgraduate (PhD or MSc) students, postdocs, young researchers, and
senior
researchers wishing to deepen their knowledge. In 2020, the broad theme of
the
school is:

“Declarative Artificial Intelligence”

As in the previous years, lectures in the summer school will be given by a
distinguished group of expert lecturers.

This year the school is part of Declarative AI 2020
(https://2020.declarativeai.net),
an event which is co-organised by SINTEF AS, University of Oslo, and
Norwegian University of Science and Technology, under the umbrella of the
SIRIUS Centre for Scalable Data Access. Due to the current situation
regarding the spread of the COVID-19 coronavirus, Declarative AI 2020 will
be held as an ONLINE event.

The school is co-located with:

- RuleML+RR: International Joint Conference on Rules and Reasoning, Virtual
29 June - 1 July, 2020
http://2020.ruleml-rr.org

- DecisionCAMP, Virtual
29 June - 1 July, 2020
https://decisioncamp2020.home.blog

The students attending the RW school are particularly encouraged to apply
to the Doctoral Consortium of RuleML+RR (deadline: 22 May, 2020).


== CONFIRMED LECTURES  ==

- Stream Reasoning: From Theory to Practice
Emanuele Della Valle (Politecnico di Milano), Riccardo Tommasini
(University of
Tartu)

- Aggregates and Generalized Atoms in Answer Set Programming
Wolfgang Faber (University of Klagenfurt)

- Knowledge Graphs: Past, Present and Future Research Directions
Aidan Hogan (University of Chile)

- Declarative Data Analysis using Limit Datalog Programs
Egor V. Kostylev (University of Oxford)

- Reasoning with Learned Knowledge
Loizos Michael (Open University of Cyprus)

- Learning Description Logic Ontologies
Ana Ozaki (Free University of Bozen-Bolzano & University of Bergen)

- Introduction to Probabilistic Ontologies
Rafael Penaloza (University of Milano-Bicocca)

- Explanation via Machine Arguing
Francesca Toni, Oana Cocarascu, Antonio Rago (Imperial College London)

- Ontology-Mediated Query Answering over Temporal Data
Michael Zakharyaschev (Birkbeck University of London)


== APPLICATIONS ==

The number of attendees will be limited and participation will depend on
submitting an application which will undergo a reviewing process.
Applications have to be submitted by filling the following form:

https://forms.gle/bDupPJyBrse1vFgP7


== IMPORTANT DATES ==

Application deadline: 1 June, 2020
Notification: 8 June, 2020
Summer school: 24-26 June, 2020


== COMMITTEE ==

Chairs

- Marco Manna, University of Calabria, Italy
- Andreas Pieris, University of Edinburgh, UK

Scientific Advisory Board

- Leopoldo Bertossi, Universidad Adolfo Ibanez, Chile
- Thomas Eiter, TU Wien, Austria
- Birte Glimm, University of Ulm, Germany
- Markus Krotzsch, TU Dresden, Germany
- Yuliya Leierler, University of Nebraska Omaha, US
- Carsten Lutz, University of Bremen, Germany
- Emanuel Sallinger, University of Oxford, UK


== CONTACT ==

For further information please contact the chairs:

- Marco Manna: mar...@un...
- Andreas Pieris: ap...@in...

[Yap-users] Property-based testing

[Paulo M. <pm...@lo...>]

Hi,

I published yesterday the third blog post on property-based testing. The solutions discussed in the posts can be used to test, besides Logtalk code, also plain Prolog and Prolog module code:

https://logtalk.org/2020/04/23/building-trust-on-property-based-testing.html

The blog is focused on logic programming best practices. Hope you enjoy reading it. Feedback and suggestions for upcoming content are most welcome.

Cheers,
Paulo

-----------------------------------------------------------------
Paulo Moura
Logtalk developer

[Yap-users] Logtalk 3.37.0 released

[Paulo M. <pm...@lo...>]

Hi,

Logtalk 3.37.0 is now available for downloading at:

https://logtalk.org/

This release adds a new meta-message to the message printing mechanism, allows the "user" pseudo-object to be used as an event monitor, fixes a reflection API bug that could result in duplicated or redundant entity operator properties, improves support for compiling modules as objects, includes significant updates to the Handbook with new and improved sections, includes new and improved glossary entries, provides new library hook objects, adds and improves notes on applying the developer tools to Prolog codebases, improves the "lgtunit" tool automation support, adds a simple example of Aspect-Oriented Programming using hot patching and event-driven programming support, and provides updated support for SWI-Prolog and YAP. For details and a complete list of changes, please consult the release notes at:

https://github.com/LogtalkDotOrg/logtalk3/blob/master/RELEASE_NOTES.md

You can show your support for Logtalk continued development and success at GitHub by giving us a star and a symbolic sponsorship:

https://github.com/LogtalkDotOrg/logtalk3

Happy logtalking!
Paulo

-----------------------------------------------------------------
Paulo Moura
Logtalk developer

[Yap-users] Logtalk 3.34.0 released

[Paulo M. <pm...@lo...>]

Hi,

Logtalk 3.34.0 is now available for downloading at:

https://logtalk.org/

This release adds support for defining predicate shorthands in "uses/2" and "use_module/2" directives, allows local operators to also be declared in scope directives to simplify compilation of included files, adds support for the legacy Prolog database built-in predicates that take a clause reference argument, improves detection of deprecated Prolog built-in predicates, improves compilation of modules as objects, includes a new and improved Handbook sections, improves "lgtunit" tool documentation and code coverage support, provides an updated "expecteds" library, includes new and updated tests for Prolog built-in predicates, includes new and updated programming examples, updates the Debian installer to define default values for the Logtalk environment variables, and provides updated support for ECLiPSe, SWI-Prolog, and YAP. For details and a complete list of changes, please consult the release notes at:

https://github.com/LogtalkDotOrg/logtalk3/blob/master/RELEASE_NOTES.md

This January makes two years of full time development with 20 releases with significant updates, a new website, and a reactivated tech blog. Your support is key for Logtalk continued development and success. Counting on you. If not already, consider giving us a star and a symbolic sponsorship at GitHub.

Happy logtalking!
Paulo

-----------------------------------------------------------------
Paulo Moura
Logtalk developer

[Yap-users] Logtalk 3.33.0 released

[Paulo M. <pm...@lo...>]

Hi,

Logtalk 3.33.0 is now available for downloading at:

https://logtalk.org/

This release adds make tool support for detecting duplicated library aliases, fixes silent loading of settings files when used to load libraries and tools, updates the documenting tool to list inherited public predicates in entity API documentation, improves tool documentation, adds new library predicates, includes fixes and improvements for libraries and tools, adds new library tests, adds new multi-threading programming examples, adds an example of using the question-asking mechanism, fixes example issues, and provides updated support for ECLiPSe, SICStus Prolog, SWI-Prolog, XSB, and YAP. For details and a complete list of changes, please consult the release notes at:

https://github.com/LogtalkDotOrg/logtalk3/blob/master/RELEASE_NOTES.md

Logtalk marketing and sponsoring goals for the current year include:

- 200 GitHub starts (currently at 153)
- 20 sponsors (currently at 3)

Next January, it will make two years of full time development with 19 releases with significant updates, a new website, and a reactivated tech blog. Your support is key for Logtalk success. Counting on you.

Happy logtalking!
Paulo



-----------------------------------------------------------------
Paulo Moura
Logtalk developer

[Yap-users] Logtalk 3.32.0 released

[Paulo M. <pm...@lo...>]

Hi,

Logtalk 3.32.0 is now available for downloading at:

https://logtalk.org/

This release adds support for multifile meta-predicates, improves some lint checks, includes fixes and improvements for embedding applications, includes documentation updates and improvements, adds support for storing settings files in the "$HOME/.config" directory, improves the "lgtunit" tool support for TAP and xUnit outputs, simplifies generation of API documentation in Sphinx format, fixes some bugs in the "diagrams" tool, adds tests for multifile meta-predicates and for the de facto standard arithmetic functions gcd/2 and sign/1, adds sample implementations of the "many worlds" design pattern using inheritance and parametric solutions, adds a new example illustrating the question asking mechanism, and provides updated support for GNU Prolog, SICStus Prolog, SWI-Prolog, and YAP. For details and a complete list of changes, please consult the release notes at:

https://github.com/LogtalkDotOrg/logtalk3/blob/master/RELEASE_NOTES.md

Last but not the least, a set of GitHub actions and workflows for Logtalk and Prolog repos is now available at:

https://github.com/logtalk-actions

These actions and workflows allow easy setup of CI/CD pipelines as illustrated by the included demo repos.

Happy logtalking!
Paulo

-----------------------------------------------------------------
Paulo Moura
Logtalk developer

[Yap-users] Logtalk 3.31.0 released

[Paulo M. <pm...@lo...>]

Hi,

Logtalk 3.31.0 is now available for downloading at:

https://logtalk.org/

This release adds new and improved lint checks for control constructs and built-in predicates, adds support for using "encoding/1" directives in included files, improves support for compiling modules as objects, includes documentation updates and improvements, includes fixes and updates for the "code_metrics" and "lgtunit" tools, includes a port of ToyCHR, updates Textadept editor support, updates the Windows installer to support Chocolatey packages, and provides portability updates for ECLiPSe, GNU Prolog, SICStus Prolog, SWI-Prolog, and YAP. For details and a complete list of changes, please consult the release notes at:

https://github.com/LogtalkDotOrg/logtalk3/blob/master/RELEASE_NOTES.md

On other news, a new guide about applying Logtalk developer tools to Prolog codebases is now available at:

https://logtalk.org/using_tools_with_prolog.html

Last but not the least, Logtalk sponsorship is now live. If you visit its repository at GitHub:

https://github.com/LogtalkDotOrg/logtalk3

at the top of the page, there's now a "Sponsor" button. Sponsorship tiers start at $2, hopefully allowing anyone to show their love and support for Logtalk. Even better, for the first year, GitHub created a Sponsors Matching Fund, which matches up to $5000 per sponsored developer in their first year of sponsorship! Counting on your to keep Logtalk a sustainable project.

Happy logtalking!
Paulo

-----------------------------------------------------------------
Paulo Moura
Logtalk developer

[Yap-users] National symbols in Yap-5.1.1

[Мурат Т. <mt...@ya...>]

I can not use in YAP Prolog 5.1.1 characters of the alphabet other than English, for example, Russian.

I have a Linux (Slackware 14.2) set up UTF-8 encoding. Compilation and installation are fine.

Does YAP Prolog 5.1.1 support UTF-8 encoding? If not, how can the sources be adjusted to work with 
characters of national alphabets other than English, for example, in the encoding CP1251 
(Russian encoding Windows). When I compile YAP Prolog on Linux with CP1251 encoding, I also can't 
work with Russian characters.

When I compile YAP Prolog 6.3 on my Linux, for some reason there is another problem - I enter a trace, 
then a question to the Prolog, and nothing else happens. Apparently this version is still in the testing and 
debugging stage, so I'm trying to use YAP Prolog 5.1.1.

Maybe I'm doing something wrong?

Ready to provide you with any additional information if needed.

Sincerely, Murat Tekeev

[Yap-users] Videos of ACAI 2018 Lectures

[Fabrizio R. <fab...@un...>]

The video recordings of all the lectures at the 2018 ACAI summer school are now available at
https://www.youtube.com/playlist?list=PLJPXEH0boeNDWTNwWTWnVffXi5XwAj1mb

The Advanced Course on AI (ACAI) is a specialized course in Artificial Intelligence sponsored by EurAI. The 2018 edition was in Ferrara, Italy on August 27th - 31st 2018
http://acai2018.unife.it/ 
The theme of the 2018 ACAI School was Statistical Relational Artificial Intelligence (StarAI).
StarAI is an emerging area that combines logical (or relational) AI and probabilistic (or statistical) AI.

The list of lectures is:

Kristian Kersting: Lifted Statistical Machine Learning
Vaishak Belle: Effective Probabilistic Logical Reasoning and Learning in Continuous Domains
Luc De Raedt: Probabilistic Programming
Paolo Frasconi: Kernels and deep networks for structured data
Fabrizio Riguzzi: Probabilistic Inductive Logic Programming
Marco Lippi: Applications of Statistical Relational Artificial Intelligence
Sriraam Natarajan: Human-in-the-loop Statistical Relational Learning
Artur d'Avila Garcez: Neural-symbolic learning
Sebastian Riedel and Pasquale Minervini: Differentiable Program Interpreters
Mathias Niepert and Alberto García Durán: Multi-Modal Neural Link Prediction


Organizers
Kristian Kersting, TU Darmstadt, Germany
Marco Lippi, University of Modena and Reggio Emilia, Italy
Sriraam Natarajan, University of Texas at Dallas, USA
Fabrizio Riguzzi, University of Ferrara, Italy

Local Organizers
Elena Bellodi, University of Ferrara, Italy
Riccardo Zese, University of Ferrara, Italy

[Yap-users] New Book: Foundations of Probabilistic Logic Programming

[Fabrizio R. <fab...@un...>]

I am pleased to announce my book:
Foundations of Probabilistic Logic Programming 
Languages, Semantics, Inference and Learning 
Author: Fabrizio Riguzzi, University of Ferrara, Italy 
Publisher: River Publishers 
Series: River Publishers Series in Software Engineering 
ISBN: 9788770220187 
e-ISBN: 9788770220170 
http://mcs.unife.it/~friguzzi/plp-book.html

Sample content: 
  Table of contents http://mcs.unife.it/~friguzzi/table-of-contents.pdf 
  Preface http://mcs.unife.it/~friguzzi/preface.pdf
  Chapter 2 http://mcs.unife.it/~friguzzi/chapter2.pdf

Get it from: 
  the publisher: http://www.riverpublishers.com/book_details.php?book_id=660
  Amazon: http://amzn.eu/d/0094M57

Abstract
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertain information. Probabilistic Logic Programming is at the intersection of two wider research fields: the integration of logic and probability and Probabilistic Programming.

Logic enables the representation of complex relations among entities while probability theory is useful for model uncertainty over attributes and relations. Combining the two is a very active field of study. Probabilistic Programming extends programming languages with probabilistic primitives that can be used to write complex probabilistic models. Algorithms for the inference and learning tasks are then provided automatically by the system.

Probabilistic Logic programming is at the same time a logic language, with its knowledge representation capabilities, and a Turing complete language, with its computation capabilities, thus providing the best of both worlds.

Since its birth, the field of Probabilistic Logic Programming has seen a steady increase of activity, with many proposals for languages and algorithms for inference and learning. Foundations of Probabilistic Logic Programming aims at providing an overview of the field with a special emphasis on languages under the Distribution Semantics, one of the most influential approaches. The book presents the main ideas for semantics, inference, and learning and highlights connections between the methods.

Many examples of the book include a link to a page of the web application http://cplint.eu where the code can be run online.

Keywords: Probabilistic logic programming, statistical relational learning, statistical relational artificial intelligence, distribution semantics, graphical models, artificial intelligence, machine learning

[Yap-users] ACAI 2018 - Call for Participation

[Fabrizio R. <fab...@un...>]

The late registration deadline (July 27th) is today.
http://acai2018.unife.it/

The Advanced Course on AI (ACAI) is a specialized course in Artificial Intelligence sponsored by EurAI. The 2018 edition will be in Ferrara, Italy on August 27th - 31st 2018, save the date!
The theme of the 2018 ACAI School is Statistical Relational Artificial Intelligence (StarAI).
StarAI is an emerging area that combines logical (or relational) AI and probabilistic (or statistical) AI.

Relational AI deals very effectively with complex domains involving many and even a varying number of entities connected by complex relationships, while statistical AI manages well the uncertainty that derives from incomplete and noisy descriptions of the domains. Both fields achieved significant successes over the last thirty years but evolved largely independently until about fifteen years ago, when the potential originating from their combination started to emerge. Statistical Relational Learning (SRL) was proposed for exploiting relational descriptions in statistical machine learning methods from the field of graphical models. Meanwhile, the scope of SRL was significantly advanced in StarAI to cover all forms of reasoning and models of AI. StarAI is nowadays an ample area encompassing many and diverse approaches.

The school includes courses on foundations of relational and statistical AI together with advanced courses on the new StarAI approaches and applications. The talks will provide theoretical background, practical examples and real applications where StarAI can play a role. Hands-on classes will be also organized where the main StarAI techniques will be applied to 'small' examples.

The list of confirmed lectures is:

Luc De Raedt: Probabilistic Programming
Paolo Frasconi: Kernels and deep networks for structured data
Sebastian Riedel and Pasquale Minervini: Differentiable Program Interpreters
Artur d'Avila Garcez: Neural-symbolic learning
Marco Lippi: Applications of Statistical Relational Artificial Intelligence
Sriraam Natarajan: Human-in-the-loop Statistical Relational Learning
Mathias Niepert and Alberto García Durán: Multi-Modal Neural Link Prediction
Kristian Kersting: Lifted Statistical Machine Learning
Fabrizio Riguzzi: Probabilistic Inductive Logic Programming
Vaishak Belle: Effective Probabilistic Logical Reasoning and Learning in Continuous Domains


Up to date information can be found at the event website
http://acai2018.unife.it/.

ACAI 2018 is part of the Relational Artificial Intelligence Days 2018 (RAID 2018, http://raid2018.unife.it/ ), which will be held in Ferrara, Italy, on August 27th 2018 - September 4th 2018. RAID includes, besides ACAI 2018, also:
- PLP 2018: 5th Workshop on Probabilistic Logic Programming, September 1st 2018, http://stoics.org.uk/plp/plp2018/ ;
- ILP 2018: 28th International Conference on Inductive Logic Programming, September 2nd - 4th 2018, http://ilp2018.unife.it/ .

Probabilistic Logic Programming (PLP) addresses the need to reason about relational domains under uncertainty arising in a variety of application domains. PLP is part of a wider current interest in probabilistic programming.  PLP 2018  aims to bring together researchers in all aspects of probabilistic logic programming, including theoretical work, system implementations and applications.

The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data. Originally focusing on the induction of logic programs, over the years it has significantly expanded and it welcomes contributions to all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.

RAID 2018 offers a very good opportunity to get up to date with the latest trends in logical and relational AI. We really hope to meet you in Ferrara!

Organizers
Kristian Kersting, TU Darmstadt, Germany
Marco Lippi, University of Modena and Reggio Emilia, Italy
Sriraam Natarajan, University of Texas at Dallas, USA
Fabrizio Riguzzi, University of Ferrara, Italy
Elena Bellodi, University of Ferrara, Italy
Tom Schrijvers, KU Leuven, Belgium
Riccardo Zese, University of Ferrara, Italy

[Yap-users] ACAI 2018 - Late Registration Deadline Today

[Fabrizio R. <fab...@un...>]

The late registration deadline (July 27th) is today.
http://acai2018.unife.it/

The Advanced Course on AI (ACAI) is a specialized course in Artificial Intelligence sponsored by EurAI. The 2018 edition will be in Ferrara, Italy on August 27th - 31st 2018, save the date!
The theme of the 2018 ACAI School is Statistical Relational Artificial Intelligence (StarAI).
StarAI is an emerging area that combines logical (or relational) AI and probabilistic (or statistical) AI.

Relational AI deals very effectively with complex domains involving many and even a varying number of entities connected by complex relationships, while statistical AI manages well the uncertainty that derives from incomplete and noisy descriptions of the domains. Both fields achieved significant successes over the last thirty years but evolved largely independently until about fifteen years ago, when the potential originating from their combination started to emerge. Statistical Relational Learning (SRL) was proposed for exploiting relational descriptions in statistical machine learning methods from the field of graphical models. Meanwhile, the scope of SRL was significantly advanced in StarAI to cover all forms of reasoning and models of AI. StarAI is nowadays an ample area encompassing many and diverse approaches.

The school includes courses on foundations of relational and statistical AI together with advanced courses on the new StarAI approaches and applications. The talks will provide theoretical background, practical examples and real applications where StarAI can play a role. Hands-on classes will be also organized where the main StarAI techniques will be applied to 'small' examples.

The list of confirmed lectures is:

Luc De Raedt: Probabilistic Programming
Paolo Frasconi: Kernels and deep networks for structured data
Sebastian Riedel: Differentiable Program Interpreters
Artur d'Avila Garcez: Neural-symbolic learning
Marco Lippi: Applications of Statistical Relational Artificial Intelligence
Sriraam Natarajan: Human-in-the-loop Statistical Relational Learning
Mathias Niepert and Alberto García Durán: Multi-Modal Neural Link Prediction
Kristian Kersting: Lifted Statistical Machine Learning
Fabrizio Riguzzi: Probabilistic Inductive Logic Programming
Vaishak Belle: Effective Probabilistic Logical Reasoning and Learning in Continuous Domains


Up to date information can be found at the event website
http://acai2018.unife.it/.

ACAI 2018 is part of the Relational Artificial Intelligence Days 2018 (RAID 2018, http://raid2018.unife.it/ ), which will be held in Ferrara, Italy, on August 27th 2018 - September 4th 2018. RAID includes, besides ACAI 2018, also:
- PLP 2018: 5th Workshop on Probabilistic Logic Programming, September 1st 2018, http://stoics.org.uk/plp/plp2018/ ;
- ILP 2018: 28th International Conference on Inductive Logic Programming, September 2nd - 4th 2018, http://ilp2018.unife.it/ .

Probabilistic Logic Programming (PLP) addresses the need to reason about relational domains under uncertainty arising in a variety of application domains. PLP is part of a wider current interest in probabilistic programming.  PLP 2018  aims to bring together researchers in all aspects of probabilistic logic programming, including theoretical work, system implementations and applications.

The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data. Originally focusing on the induction of logic programs, over the years it has significantly expanded and it welcomes contributions to all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.

RAID 2018 offers a very good opportunity to get up to date with the latest trends in logical and relational AI. We really hope to meet you in Ferrara!

Organizers
Kristian Kersting, TU Darmstadt, Germany
Marco Lippi, University of Modena and Reggio Emilia, Italy
Sriraam Natarajan, University of Texas at Dallas, USA
Fabrizio Riguzzi, University of Ferrara, Italy
Elena Bellodi, University of Ferrara, Italy
Tom Schrijvers, KU Leuven, Belgium
Riccardo Zese, University of Ferrara, Italy

[Yap-users] ACAI 2018 - Late Registration Deadline Approaching

[Fabrizio R. <fab...@un...>]

The later registration deadline (July 27th) is approaching.
http://acai2018.unife.it/

The Advanced Course on AI (ACAI) is a specialized course in Artificial Intelligence sponsored by EurAI. The 2018 edition will be in Ferrara, Italy on August 27th - 31st 2018, save the date!
The theme of the 2018 ACAI School is Statistical Relational Artificial Intelligence (StarAI).
StarAI is an emerging area that combines logical (or relational) AI and probabilistic (or statistical) AI.

Relational AI deals very effectively with complex domains involving many and even a varying number of entities connected by complex relationships, while statistical AI manages well the uncertainty that derives from incomplete and noisy descriptions of the domains. Both fields achieved significant successes over the last thirty years but evolved largely independently until about fifteen years ago, when the potential originating from their combination started to emerge. Statistical Relational Learning (SRL) was proposed for exploiting relational descriptions in statistical machine learning methods from the field of graphical models. Meanwhile, the scope of SRL was significantly advanced in StarAI to cover all forms of reasoning and models of AI. StarAI is nowadays an ample area encompassing many and diverse approaches.

The school includes courses on foundations of relational and statistical AI together with advanced courses on the new StarAI approaches and applications. The talks will provide theoretical background, practical examples and real applications where StarAI can play a role. Hands-on classes will be also organized where the main StarAI techniques will be applied to 'small' examples.

The list of confirmed lectures is:

Luc De Raedt: Probabilistic Programming
Paolo Frasconi: Kernels and deep networks for structured data
Sebastian Riedel: Differentiable Program Interpreters
Artur d'Avila Garcez: Neural-symbolic learning
Marco Lippi: Applications of Statistical Relational Artificial Intelligence
Sriraam Natarajan: Human-in-the-loop Statistical Relational Learning
Mathias Niepert and Alberto García Durán: Multi-Modal Neural Link Prediction
Kristian Kersting: Lifted Statistical Machine Learning
Fabrizio Riguzzi: Probabilistic Inductive Logic Programming
Vibhav Gogate: Lifted Systematic Search and Sampling


Up to date information can be found at the event website
http://acai2018.unife.it/.

ACAI 2018 is part of the Relational Artificial Intelligence Days 2018 (RAID 2018, http://raid2018.unife.it/ ), which will be held in Ferrara, Italy, on August 27th 2018 - September 4th 2018. RAID includes, besides ACAI 2018, also:
- PLP 2018: 5th Workshop on Probabilistic Logic Programming, September 1st 2018, http://stoics.org.uk/plp/plp2018/ ;
- ILP 2018: 28th International Conference on Inductive Logic Programming, September 2nd - 4th 2018, http://ilp2018.unife.it/ .

Probabilistic Logic Programming (PLP) addresses the need to reason about relational domains under uncertainty arising in a variety of application domains. PLP is part of a wider current interest in probabilistic programming.  PLP 2018  aims to bring together researchers in all aspects of probabilistic logic programming, including theoretical work, system implementations and applications.

The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data. Originally focusing on the induction of logic programs, over the years it has significantly expanded and it welcomes contributions to all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.

RAID 2018 offers a very good opportunity to get up to date with the latest trends in logical and relational AI. We really hope to meet you in Ferrara!

Organizers
Kristian Kersting, TU Darmstadt, Germany
Marco Lippi, University of Modena and Reggio Emilia, Italy
Sriraam Natarajan, University of Texas at Dallas, USA
Fabrizio Riguzzi, University of Ferrara, Italy
Elena Bellodi, University of Ferrara, Italy
Tom Schrijvers, KU Leuven, Belgium
Riccardo Zese, University of Ferrara, Italy

[Yap-users] ACAI 2018 - Early Registration Deadline Approaching

[Fabrizio R. <fab...@un...>]

The early registration deadline (June th) is approaching.
http://acai2018.unife.it/
Important dates:
15 June early registration deadline
27 July late registration deadline

The Advanced Course on AI (ACAI) is a specialized course in Artificial Intelligence sponsored by EurAI. The 2018 edition will be in Ferrara, Italy on August 27th - 31st 2018, save the date!
The theme of the 2018 ACAI School is Statistical Relational Artificial Intelligence (StarAI).
StarAI is an emerging area that combines logical (or relational) AI and probabilistic (or statistical) AI.

Relational AI deals very effectively with complex domains involving many and even a varying number of entities connected by complex relationships, while statistical AI manages well the uncertainty that derives from incomplete and noisy descriptions of the domains. Both fields achieved significant successes over the last thirty years but evolved largely independently until about fifteen years ago, when the potential originating from their combination started to emerge. Statistical Relational Learning (SRL) was proposed for exploiting relational descriptions in statistical machine learning methods from the field of graphical models. Meanwhile, the scope of SRL was significantly advanced in StarAI to cover all forms of reasoning and models of AI. StarAI is nowadays an ample area encompassing many and diverse approaches.

The school includes courses on foundations of relational and statistical AI together with advanced courses on the new StarAI approaches and applications. The talks will provide theoretical background, practical examples and real applications where StarAI can play a role. Hands-on classes will be also organized where the main StarAI techniques will be applied to 'small' examples.

The list of confirmed lectures is:

Luc De Raedt: Probabilistic Programming
Paolo Frasconi: Kernels and deep networks for structured data
Sebastian Riedel: Differentiable Program Interpreters
Artur d'Avila Garcez: Neural-symbolic learning
Marco Lippi: Applications of Statistical Relational Artificial Intelligence
Sriraam Natarajan: Human-in-the-loop Statistical Relational Learning
Mathias Niepert and Alberto García Durán: Multi-Modal Neural Link Prediction
Kristian Kersting: Lifted Statistical Machine Learning
Fabrizio Riguzzi: Probabilistic Inductive Logic Programming
Vibhav Gogate: Lifted Systematic Search and Sampling
David Poole: TBA

Up to date information can be found at the event website
http://acai2018.unife.it/.

ACAI 2018 is part of the Relational Artificial Intelligence Days 2018 (RAID 2018, http://raid2018.unife.it/ ), which will be held in Ferrara, Italy, on August 27th 2018 - September 4th 2018. RAID includes, besides ACAI 2018, also:
- PLP 2018: 5th Workshop on Probabilistic Logic Programming, September 1st 2018, http://stoics.org.uk/plp/plp2018/ ;
- ILP 2018: 28th International Conference on Inductive Logic Programming, September 2nd - 4th 2018, http://ilp2018.unife.it/ .

Probabilistic Logic Programming (PLP) addresses the need to reason about relational domains under uncertainty arising in a variety of application domains. PLP is part of a wider current interest in probabilistic programming.  PLP 2018  aims to bring together researchers in all aspects of probabilistic logic programming, including theoretical work, system implementations and applications.

The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data. Originally focusing on the induction of logic programs, over the years it has significantly expanded and it welcomes contributions to all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.

RAID 2018 offers a very good opportunity to get up to date with the latest trends in logical and relational AI. We really hope to meet you in Ferrara!

Organizers
Kristian Kersting, TU Darmstadt, Germany
Marco Lippi, University of Modena and Reggio Emilia, Italy
Sriraam Natarajan, University of Texas at Dallas, USA
Fabrizio Riguzzi, University of Ferrara, Italy
Elena Bellodi, University of Ferrara, Italy
Tom Schrijvers, KU Leuven, Belgium
Riccardo Zese, University of Ferrara, Italy

[Yap-users] ACAI 2018 - Registration and travel grants

[Fabrizio R. <fab...@un...>]

The first cutoff date for travel grants is approaching.
http://acai2018.unife.it/
Important dates:
30 May first cutoff date for travel grants
15 June early registration deadline
30 June second cutoff date for travel grants
27 July late registration deadline

The Advanced Course on AI (ACAI) is a specialized course in Artificial Intelligence sponsored by EurAI. The 2018 edition will be in Ferrara, Italy on August 27th - 31st 2018, save the date!
The theme of the 2018 ACAI School is Statistical Relational Artificial Intelligence (StarAI).
StarAI is an emerging area that combines logical (or relational) AI and probabilistic (or statistical) AI.

Relational AI deals very effectively with complex domains involving many and even a varying number of entities connected by complex relationships, while statistical AI manages well the uncertainty that derives from incomplete and noisy descriptions of the domains. Both fields achieved significant successes over the last thirty years but evolved largely independently until about fifteen years ago, when the potential originating from their combination started to emerge. Statistical Relational Learning (SRL) was proposed for exploiting relational descriptions in statistical machine learning methods from the field of graphical models. Meanwhile, the scope of SRL was significantly advanced in StarAI to cover all forms of reasoning and models of AI. StarAI is nowadays an ample area encompassing many and diverse approaches.

The school includes courses on foundations of relational and statistical AI together with advanced courses on the new StarAI approaches and applications. The talks will provide theoretical background, practical examples and real applications where StarAI can play a role. Hands-on classes will be also organized where the main StarAI techniques will be applied to 'small' examples.

The list of confirmed lectures is:

Luc De Raedt: Probabilistic Programming
Paolo Frasconi: Kernels and deep networks for structured data
Sebastian Riedel: Differentiable Program Interpreters
Artur d'Avila Garcez: Neural-symbolic learning
Marco Lippi: Applications of Statistical Relational Artificial Intelligence
Sriraam Natarajan: Human-in-the-loop Statistical Relational Learning
Mathias Niepert and Alberto García Durán: Multi-Modal Neural Link Prediction
Kristian Kersting: Lifted Statistical Machine Learning
Fabrizio Riguzzi: Probabilistic Inductive Logic Programming
Vibhav Gogate: Lifted Systematic Search and Sampling
David Poole: TBA

Up to date information can be found at the event website
http://acai2018.unife.it/.

ACAI 2018 is part of the Relational Artificial Intelligence Days 2018 (RAID 2018, http://raid2018.unife.it/ ), which will be held in Ferrara, Italy, on August 27th 2018 - September 4th 2018. RAID includes, besides ACAI 2018, also:
- PLP 2018: 5th Workshop on Probabilistic Logic Programming, September 1st 2018, http://stoics.org.uk/plp/plp2018/ ;
- ILP 2018: 28th International Conference on Inductive Logic Programming, September 2nd - 4th 2018, http://ilp2018.unife.it/ .

Probabilistic Logic Programming (PLP) addresses the need to reason about relational domains under uncertainty arising in a variety of application domains. PLP is part of a wider current interest in probabilistic programming.  PLP 2018  aims to bring together researchers in all aspects of probabilistic logic programming, including theoretical work, system implementations and applications.

The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data. Originally focusing on the induction of logic programs, over the years it has significantly expanded and it welcomes contributions to all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.

RAID 2018 offers a very good opportunity to get up to date with the latest trends in logical and relational AI. We really hope to meet you in Ferrara!

Organizers
Kristian Kersting, TU Darmstadt, Germany
Marco Lippi, University of Modena and Reggio Emilia, Italy
Sriraam Natarajan, University of Texas at Dallas, USA
Fabrizio Riguzzi, University of Ferrara, Italy
Elena Bellodi, University of Ferrara, Italy
Tom Schrijvers, KU Leuven, Belgium
Riccardo Zese, University of Ferrara, Italy

[Yap-users] ACAI 2018 - Registration and travel grants

[Fabrizo R. <fab...@un...>]

UPDATE: registration fees have been published and registration is now open. 
Travel grants from EurAI are available.
http://acai2018.unife.it/



The Advanced Course on AI (ACAI) is a specialized course in Artificial Intelligence sponsored by EurAI. The 2018 edition will be in Ferrara, Italy on August 27th - 31st 2018, save the date!
The theme of the 2018 ACAI School is Statistical Relational Artificial Intelligence (StarAI).
StarAI is an emerging area that combines logical (or relational) AI and probabilistic (or statistical) AI.

Relational AI deals very effectively with complex domains involving many and even a varying number of entities connected by complex relationships, while statistical AI manages well the uncertainty that derives from incomplete and noisy descriptions of the domains. Both fields achieved significant successes over the last thirty years but evolved largely independently until about fifteen years ago, when the potential originating from their combination started to emerge. Statistical Relational Learning (SRL) was proposed for exploiting relational descriptions in statistical machine learning methods from the field of graphical models. Meanwhile, the scope of SRL was significantly advanced in StarAI to cover all forms of reasoning and models of AI. StarAI is nowadays an ample area encompassing many and diverse approaches.

The school includes courses on foundations of relational and statistical AI together with advanced courses on the new StarAI approaches and applications. The talks will provide theoretical background, practical examples and real applications where StarAI can play a role. Hands-on classes will be also organized where the main StarAI techniques will be applied to 'small' examples.

The list of confirmed lectures is:

Luc De Raedt: Probabilistic Programming
Paolo Frasconi: Kernels and deep networks for structured data
Sebastian Riedel: Differentiable Program Interpreters
Artur d'Avila Garcez: Neural-symbolic learning
Marco Lippi: Applications of Statistical Relational Artificial Intelligence
Sriraam Natarajan: Human-in-the-loop Statistical Relational Learning
Mathias Niepert and Alberto García Durán: Multi-Modal Neural Link Prediction
Kristian Kersting: Lifted Statistical Machine Learning
Fabrizio Riguzzi: Probabilistic Inductive Logic Programming
Vibhav Gogate: Lifted Systematic Search and Sampling
David Poole: TBA

Up to date information can be found at the event website
http://acai2018.unife.it/.
The registration fees will be published shortly.

ACAI 2018 is part of the Relational Artificial Intelligence Days 2018 (RAID 2018, http://raid2018.unife.it/ ), which will be held in Ferrara, Italy, on August 27th 2018 - September 4th 2018. RAID includes, besides ACAI 2018, also:
- PLP 2018: 5th Workshop on Probabilistic Logic Programming, September 1st 2018, http://stoics.org.uk/plp/plp2018/ ;
- ILP 2018: 28th International Conference on Inductive Logic Programming, September 2nd - 4th 2018, http://ilp2018.unife.it/ .

Probabilistic Logic Programming (PLP) addresses the need to reason about relational domains under uncertainty arising in a variety of application domains. PLP is part of a wider current interest in probabilistic programming.  PLP 2018  aims to bring together researchers in all aspects of probabilistic logic programming, including theoretical work, system implementations and applications.

The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data. Originally focusing on the induction of logic programs, over the years it has significantly expanded and it welcomes contributions to all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.

RAID 2018 offers a very good opportunity to get up to date with the latest trends in logical and relational AI. We really hope to meet you in Ferrara!

Organizers
Kristian Kersting, TU Darmstadt, Germany
Marco Lippi, University of Modena and Reggio Emilia, Italy
Sriraam Natarajan, University of Texas at Dallas, USA
Fabrizio Riguzzi, University of Ferrara, Italy
Elena Bellodi, University of Ferrara, Italy
Tom Schrijvers, KU Leuven, Belgium
Riccardo Zese, University of Ferrara, Italy

[Yap-users] ACAI 2018 Summer School on Statistical Relational Artificial Intelligence

[Fabrizo R. <fab...@un...>]

The Advanced Course on AI (ACAI) is a specialized course in Artificial Intelligence sponsored by EurAI. The 2018 edition will be in Ferrara, Italy on August 27th - 31st 2018, save the date!
The theme of the 2018 ACAI School is Statistical Relational Artificial Intelligence (StarAI).
StarAI is an emerging area that combines logical (or relational) AI and probabilistic (or statistical) AI.

Relational AI deals very effectively with complex domains involving many and even a varying number of entities connected by complex relationships, while statistical AI manages well the uncertainty that derives from incomplete and noisy descriptions of the domains. Both fields achieved significant successes over the last thirty years but evolved largely independently until about fifteen years ago, when the potential originating from their combination started to emerge. Statistical Relational Learning (SRL) was proposed for exploiting relational descriptions in statistical machine learning methods from the field of graphical models. Meanwhile, the scope of SRL was significantly advanced in StarAI to cover all forms of reasoning and models of AI. StarAI is nowadays an ample area encompassing many and diverse approaches.

The school includes courses on foundations of relational and statistical AI together with advanced courses on the new StarAI approaches and applications. The talks will provide theoretical background, practical examples and real applications where StarAI can play a role. Hands-on classes will be also organized where the main StarAI techniques will be applied to 'small' examples.

The list of confirmed lectures is:

Luc De Raedt: Probabilistic Programming
Paolo Frasconi: Kernels and deep networks for structured data
Sebastian Riedel: Differentiable Program Interpreters
Artur d'Avila Garcez: Neural-symbolic learning
Marco Lippi: Applications of Statistical Relational Artificial Intelligence
Sriraam Natarajan: Human-in-the-loop Statistical Relational Learning
Mathias Niepert and Alberto García Durán: Multi-Modal Neural Link Prediction
Kristian Kersting: Lifted Statistical Machine Learning
Fabrizio Riguzzi: Probabilistic Inductive Logic Programming
Vibhav Gogate: TBA
David Poole: TBA

Up to date information can be found at the event website
http://acai2018.unife.it/.
The registration fees will be published shortly.

ACAI 2018 is part of the Relational Artificial Intelligence Days 2018 (RAID 2018, http://raid2018.unife.it/ ), which will be held in Ferrara, Italy, on August 27th 2018 - September 4th 2018. RAID includes, besides ACAI 2018, also:
- PLP 2018: 5th Workshop on Probabilistic Logic Programming, September 1st 2018, http://stoics.org.uk/plp/plp2018/ ;
- ILP 2018: 28th International Conference on Inductive Logic Programming, September 2nd - 4th 2018, http://ilp2018.unife.it/ .

Probabilistic Logic Programming (PLP) addresses the need to reason about relational domains under uncertainty arising in a variety of application domains. PLP is part of a wider current interest in probabilistic programming.  PLP 2018  aims to bring together researchers in all aspects of probabilistic logic programming, including theoretical work, system implementations and applications.

The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data. Originally focusing on the induction of logic programs, over the years it has significantly expanded and it welcomes contributions to all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.

RAID 2018 offers a very good opportunity to get up to date with the latest trends in logical and relational AI. We really hope to meet you in Ferrara!

Organizers
Kristian Kersting, TU Darmstadt, Germany
Marco Lippi, University of Modena and Reggio Emilia, Italy
Sriraam Natarajan, University of Texas at Dallas, USA
Fabrizio Riguzzi, University of Ferrara, Italy
Elena Bellodi, University of Ferrara, Italy
Tom Schrijvers, KU Leuven, Belgium
Riccardo Zese, University of Ferrara, Italy

[Yap-users] ACAI 2018 Summer School on Statistical Relational Artificial Intelligence

[Fabrizo R. <fab...@un...>]

The Advanced Course on AI (ACAI) is a specialized course in Artificial Intelligence sponsored by EurAI. The 2018 edition will be in Ferrara, Italy on August 27th - 31st 2018, save the date!
The theme of the 2018 ACAI School is Statistical Relational Artificial Intelligence (StarAI).
StarAI is an emerging area that combines logical (or relational) AI and probabilistic (or statistical) AI.

Relational AI deals very effectively with complex domains involving many and even a varying number of entities connected by complex relationships, while statistical AI manages well the uncertainty that derives from incomplete and noisy descriptions of the domains. Both fields achieved significant successes over the last thirty years but evolved largely independently until about fifteen years ago, when the potential originating from their combination started to emerge. Statistical Relational Learning (SRL) was proposed for exploiting relational descriptions in statistical machine learning methods from the field of graphical models. Meanwhile, the scope of SRL was significantly advanced in StarAI to cover all forms of reasoning and models of AI. StarAI is nowadays an ample area encompassing many and diverse approaches.

The school includes courses on foundations of relational and statistical AI together with advanced courses on the new StarAI approaches and applications. The talks will provide theoretical background, practical examples and real applications where StarAI can play a role. Hands-on classes will be also organized where the main StarAI techniques will be applied to 'small' examples.

The list of confirmed lectures is:

Luc De Raedt: Probabilistic Programming
Paolo Frasconi: Kernels and deep networks for structured data
Sebastian Riedel: Differentiable Program Interpreters
Artur d'Avila Garcez: Neural-symbolic learning
Marco Lippi: Applications of Statistical Relational Artificial Intelligence
Sriraam Natarajan: Human-in-the-loop Statistical Relational Learning
Mathias Niepert and Alberto García Durán: Multi-Modal Neural Link Prediction
Kristian Kersting: Lifted Statistical Machine Learning
Fabrizio Riguzzi: Probabilistic Inductive Logic Programming

Up to date information can be found at the event website
http://acai2018.unife.it/.
The registration fees will be published shortly.

ACAI 2018 is part of the Relational Artificial Intelligence Days 2018 (RAID 2018, http://raid2018.unife.it/ ), which will be held in Ferrara, Italy, on August 27th 2018 - September 4th 2018. RAID includes, besides ACAI 2018, also:
- PLP 2018: 5th Workshop on Probabilistic Logic Programming, September 1st 2018, http://stoics.org.uk/plp/plp2018/ ;
- ILP 2018: 28th International Conference on Inductive Logic Programming, September 2nd - 4th 2018, http://ilp2018.unife.it/ .

Probabilistic Logic Programming (PLP) addresses the need to reason about relational domains under uncertainty arising in a variety of application domains. PLP is part of a wider current interest in probabilistic programming.  PLP 2018  aims to bring together researchers in all aspects of probabilistic logic programming, including theoretical work, system implementations and applications.

The ILP conference series, started in 1991, is the premier international forum for learning from structured or semi-structured relational data. Originally focusing on the induction of logic programs, over the years it has significantly expanded and it welcomes contributions to all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.

RAID 2018 offers a very good opportunity to get up to date with the latest trends in logical and relational AI. We really hope to meet you in Ferrara!

Organizers
Kristian Kersting, TU Darmstadt, Germany
Marco Lippi, University of Modena and Reggio Emilia, Italy
Sriraam Natarajan, University of Texas at Dallas, USA
Fabrizio Riguzzi, University of Ferrara, Italy
Elena Bellodi, University of Ferrara, Italy
Tom Schrijvers, KU Leuven, Belgium
Riccardo Zese, University of Ferrara, Italy