toss-devel Mailing List for Toss (Page 2)
Status: Beta
Brought to you by:
lukaszkaiser
Menu
▾
▴
toss-devel — Toss develpment discussion
You can subscribe to this list here.
| 2004 |
Jan
|
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
(1) |
Sep
|
Oct
|
Nov
|
Dec
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2005 |
Jan
(1) |
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
| 2009 |
Jan
|
Feb
|
Mar
(1) |
Apr
|
May
|
Jun
|
Jul
|
Aug
(17) |
Sep
(34) |
Oct
|
Nov
|
Dec
|
| 2010 |
Jan
|
Feb
(100) |
Mar
(122) |
Apr
(5) |
May
|
Jun
(17) |
Jul
(36) |
Aug
(9) |
Sep
(111) |
Oct
(92) |
Nov
(76) |
Dec
(26) |
| 2011 |
Jan
(3) |
Feb
(35) |
Mar
(36) |
Apr
(10) |
May
(9) |
Jun
(2) |
Jul
(3) |
Aug
(2) |
Sep
|
Oct
(7) |
Nov
(12) |
Dec
|
| 2012 |
Jan
(19) |
Feb
(1) |
Mar
(4) |
Apr
(1) |
May
(6) |
Jun
(69) |
Jul
(21) |
Aug
(12) |
Sep
(14) |
Oct
(1) |
Nov
(3) |
Dec
|
| 2013 |
Jan
(6) |
Feb
(1) |
Mar
(6) |
Apr
(3) |
May
(6) |
Jun
(1) |
Jul
|
Aug
|
Sep
|
Oct
(2) |
Nov
(3) |
Dec
|
| 2014 |
Jan
|
Feb
|
Mar
(6) |
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
| 2015 |
Jan
(4) |
Feb
|
Mar
|
Apr
|
May
|
Jun
|
Jul
|
Aug
|
Sep
|
Oct
|
Nov
(1) |
Dec
(3) |
| 2016 |
Jan
(6) |
Feb
(1) |
Mar
(3) |
Apr
(1) |
May
(3) |
Jun
(1) |
Jul
(1) |
Aug
(3) |
Sep
(2) |
Oct
(1) |
Nov
(1) |
Dec
(1) |
| 2017 |
Jan
|
Feb
(2) |
Mar
(1) |
Apr
|
May
|
Jun
|
Jul
(2) |
Aug
|
Sep
|
Oct
|
Nov
|
Dec
|
|
From: Vimal S. <vi...@mo...> - 2013-05-22 16:07:19
|
<HEAD> <META http-equiv=Content-Type content="text/html; charset=windows-1252"> <META content="MSHTML 6.00.2900.2180" name=GENERATOR></HEAD> <BODY><FONT face="Arial, Helvetica, sans-serif" size=2> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">Hello, <?xml:namespace prefix = o ns = "urn:schemas-microsoft-com:office:office" /><o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">My name is Vimal Suresh, from Monster Free Apps. <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">I am contacting you to make sure you are aware of <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">"Monster Free Apps" a free app per day type app for <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">iOS devices that can put your application in front of <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">hundreds of thousands of IOS users. GREE, Funzio,<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">TinyCo, Kabam, Gamevil USA, Animoca and hundreds <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">more have used our service.<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">Here’s a recent testimonial from a client:<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"> **<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">"Monster Free Apps has done wonders for the <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">exposure of our first game, "Prison Run" We ended <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">up ranking in over 85 app stores around the world <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">and even held the top iPad Puzzle Game in 11 <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">countries, including in the U.K. We'll be making sure <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">Monster Free Apps is used with every new game <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">and app we come out with. Awesome service!!!" <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">- Paul McDonald / Jack Apps Media LLC<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"> **<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">How does it work? It's pretty straight forward. We <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">feature your app in Monster Free Apps as the <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">featured app of the day. <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">Our users get push notifications about your app <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">being featured. They download your app if it is <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">appealing to them. No incentivized downloads. <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">Quality users that want your app, and your app <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">climbs the ranks.<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">If you would like to know more, please ask for our <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">“Media Kit,” As it outlines our rates and goes over <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">dozens of questions you are likely to have. <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">If you are not right point of contact for this matter, I <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">would appreciate if you can pass this on to the <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">appropriate person.<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">I look forward to hearing from you soon.<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"> <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">Regards,<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"> <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">Vimal Suresh | Advertising Coordinator | MonsterFreeApps<o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: #1f497d; FONT-FAMILY: 'Calibri','sans-serif'"><o:p> </o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'"> <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">PS: So that you are not caught off guard, we don't <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">typically have quick availability. Clients are booking <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">out weeks in advance at the moment, so I'd love to <o:p></o:p></SPAN></P> <P style="MARGIN: 0in 0in 0pt"><SPAN style="FONT-SIZE: 11pt; COLOR: black; FONT-FAMILY: 'Calibri','sans-serif'">reserve something for your company now.<o:p></o:p></SPAN></P></FONT></BODY> |
|
From: Lukasz S. <luk...@gm...> - 2013-05-19 19:22:55
|
TrG:0:TranslateGameExtra:0:connect5... tested connect5 in 1.688188 seconds ok TrG:0:TranslateGameExtra:1:connect4... tested connect4 in 1.973074 seconds ok TrG:0:TranslateGameExtra:2:pawn_whopping... tested pawn_whopping in 5.450739 seconds ok TrG:0:TranslateGameExtra:3:breakthrough... tested breakthrough in 31.144674 seconds ok TrG:0:TranslateGameExtra:4:pacman3p... FAIL TrG:0:TranslateGameExtra:5:chinesecheckers3... tested chinesecheckers3 in 273.177435 seconds ok TrG:0:TranslateGameExtra:6:asteroids-scrambled... make: *** [GGPTestsExtra] Przerwanie |
|
From: <ro...@sw...> - 2013-05-16 14:45:51
|
Join today and find the perfect sex date. http://redirect.brinstanroom.com 589849 nyerlx |
|
From: Lukasz S. <luk...@gm...> - 2013-04-21 20:31:36
|
http://arxiv.org/abs/1304.5159 Interactive POMDP Lite: Towards Practical Planning to Predict and Exploit Intentions for Interacting with Self-Interested Agents Trong Nghia Hoang <http://arxiv.org/find/cs/1/au:+Hoang_T/0/1/0/all/0/1>, Kian Hsiang Low <http://arxiv.org/find/cs/1/au:+Low_K/0/1/0/all/0/1> (Submitted on 18 Apr 2013) A key challenge in non-cooperative multi-agent systems is that of developing efficient planning algorithms for intelligent agents to interact and perform effectively among boundedly rational, self-interested agents (e.g., humans). The practicality of existing works addressing this challenge is being undermined due to either the restrictive assumptions of the other agents' behavior, the failure in accounting for their rationality, or the prohibitively expensive cost of modeling and predicting their intentions. To boost the practicality of research in this field, we investigate how intention prediction can be efficiently exploited and made practical in planning, thereby leading to efficient intention-aware planning frameworks capable of predicting the intentions of other agents and acting optimally with respect to their predicted intentions. We show that the performance losses incurred by the resulting planning policies are linearly bounded by the error of intention prediction. Empirical evaluations through a series of stochastic games demonstrate that our policies can achieve better and more robust performance than the state-of-the-art algorithms. http://arxiv.org/abs/1304.2024 A General Framework for Interacting Bayes-Optimally with Self-Interested Agents using Arbitrary Parametric Model and Model Prior Trong Nghia Hoang <http://arxiv.org/find/cs/1/au:+Hoang_T/0/1/0/all/0/1>, Kian Hsiang Low <http://arxiv.org/find/cs/1/au:+Low_K/0/1/0/all/0/1> (Submitted on 7 Apr 2013 (v1 <http://arxiv.org/abs/1304.2024v1>), last revised 18 Apr 2013 (this version, v2)) Recent advances in Bayesian reinforcement learning (BRL) have shown that Bayes-optimality is theoretically achievable by modeling the environment's latent dynamics using Flat-Dirichlet-Multinomial (FDM) prior. In self-interested multi-agent environments, the transition dynamics are mainly controlled by the other agent's stochastic behavior for which FDM's independence and modeling assumptions do not hold. As a result, FDM does not allow the other agent's behavior to be generalized across different states nor specified using prior domain knowledge. To overcome these practical limitations of FDM, we propose a generalization of BRL to integrate the general class of parametric models and model priors, thus allowing practitioners' domain knowledge to be exploited to produce a fine-grained and compact representation of the other agent's behavior. Empirical evaluation shows that our approach outperforms existing multi-agent reinforcement learning algorithms. |
|
From: Lukasz S. <luk...@gm...> - 2013-04-20 13:14:56
|
---------- Forwarded message ----------
From: Marcus Hutter <mar...@gm...>
Date: Fri, Apr 19, 2013 at 11:34 AM
Subject: [AGI-group] Fwd: IJCAI 2013 Angry Birds AI Competition -- Call for
Participation
To: art...@go...
*******************************************************************
Call for Participation
IJCAI 2013 Angry Birds AI Competition
http://www.aibirds.org
Beijing, China, 6-9 August 2013
*******************************************************************
Angry Birds is a popular video game where players shoot birds in order
to destroy pigs protected by complicated structures. The task of this
competition is to develop an intelligent Angry Birds playing agent that
is able to successfully play the game autonomously and without human
intervention. The long term goal is to build AI agents that can play new
levels better than the best human players. In order to successfully
solve this challenge, participants can benefit from combining different
areas of AI such as computer vision, knowledge representation and
reasoning, planning, heuristic search, and machine learning.
Successfully integrating methods from these areas is one of the great
challenges of AI.
Game Playing Software
==================
The organizers have provided a basic game playing software and a sample
agent. Participants are free to adapt this software. The software can be
downloaded at http://www.aibirds.org. On this website, we also offer a
discussion forum for participants, benchmarks and other relevant
information.
Prizes
=====
The teams of the three best agents will receive a prize as well as a
certificate.
* First prize: USD 1500
* Second prize: USD 1000
* Third prize: USD 500
All participants of the finals will also receive a certificate.
Symposium on AI in Angry Birds
=========================
During the competition, there will be an opportunity to present original
scientific work related to the problems of developing an Angry Birds
playing agent. Please refer to the Call for Papers at http://www.aibirds.org
Man vs Machine Challenge
====================
On 9 August 2013, everyone is invited to compete against the best AI
agents.
The winner of this challenge, man or machine, will receive USD 500 and
a certificate.
Important Dates
============
* Early registration: 30 June 2013
* Agent submissions (qualification round): 5 August 2013
* Final agent submission: 8 August 2013
* Competition: 6-7 August (qualification), 8 August (finals)
* Paper submissions: 30 June 2013
* Acceptance notification: 14 July 2013
* Camera ready deadline: 28 July 2013
Organizers
=========
* Jochen Renz, Australian National University
* Stephen Gould, Australian National University
* XiaoYu (Gary) Ge, Australian National University
All enquiries should be made by email to
angrybirdscompetition@gmail.**com <ang...@gm...>.
--
You received this message because you are subscribed to the Google Groups
"Artificial General Intelligence" group.
To unsubscribe from this group and stop receiving emails from it, send an
email to artificial-general-**intelligence+unsubscribe@**googlegroups.com<artificial-general-intelligence%2Bu...@go...>
.
For more options, visit
https://groups.google.com/**groups/opt_out<https://groups.google.com/groups/opt_out>
.
|
|
From: Lukasz S. <luk...@gm...> - 2013-04-03 01:10:54
|
http://remi.coulom.free.fr/Amsterdam2007/MMGoPatterns.pdf Rémi Coulom Université Charles de Gaulle, INRIA SEQUEL, CNRS GRAPPA, Lille, France Abstract. Move patterns are an essential method to incorporate do- main knowledge into Go-playing programs. This paper presents a new Bayesian technique for supervised learning of such patterns from game records, based on a generalization of Elo ratings. Each sample move in the training data is considered as a victory of a team of pattern features. Elo ratings of individual pattern features are computed from these victo- ries, and can be used in previously unseen positions to compute a prob- ability distribution over legal moves. In this approach, several pattern features may be combined, without an exponential cost in the number of features. [...] |
|
From: Lukasz S. <luk...@gm...> - 2013-03-26 22:05:40
|
On Tue, Mar 26, 2013 at 11:00 PM, Lukasz Kaiser <luk...@gm...>wrote: > Hi, > > finally I compiled and tested the long-overdue > Toss release 0.9. It is on sourceforge now, so > feel free to download and check if everything is ok :). > > Best! > > Lukasz > > Bravo! |
|
From: Lukasz K. <luk...@gm...> - 2013-03-26 22:01:35
|
Hi, finally I compiled and tested the long-overdue Toss release 0.9. It is on sourceforge now, so feel free to download and check if everything is ok :). Best! Lukasz |
|
From: Lukasz S. <luk...@gm...> - 2013-03-25 09:27:40
|
A paper on a learning system using traditional RL applied to multiple video games. http://cs229.stanford.edu/proj2012/JohnsonRobertsFisher-LearningToPlay2DVideoGames.pdf |
|
From: Lukasz S. <luk...@gm...> - 2013-03-25 09:24:44
|
Potential Toss developers might benefit from this functional programming course. Note though that it is not intended with Toss in mind. http://www.ii.uni.wroc.pl/~lukstafi/pmwiki/index.php?n=Functional.Functional |
|
From: Lukasz S. <luk...@gm...> - 2013-03-01 11:22:04
|
Sorry about the noise, unintentional ;-) On Fri, Mar 1, 2013 at 12:05 PM, Google+ <nor...@pl...>wrote: |
|
From: Lukasz S. <luk...@gm...> - 2013-02-11 20:45:22
|
Hi, I'd like to remind you of current and upcoming courses relevant to Toss: (1) https://www.coursera.org/course/aiplan "Artificial Intelligence Planning" covers "Toss with single player" scenarios. It has already got interesting with backward planning and plan-space planning. (2) https://www.coursera.org/course/ggp "General Game Playing" starts in April. (3) https://www.coursera.org/course/machlearning "Machine Learning" covers the relevant topic "Learning sets of rules and logic programs" in week 3. I thought it would mention "probabilistic logic programming" (since it's by the author of Markov Logic Networks), but that's absent from its topics. (No date yet.) |
|
From: Lukasz K. <luk...@gm...> - 2013-01-21 22:54:47
|
Hi. We were all thinking a lot recently about a more quantitative Toss, and I write this mail to sum up what was said so far and to open a thread for further thought and discussion. The problem starts with the fact that the world is not always discrete. We want to do vision, so we need various quantities. These can be probabilities, colors, movements and other things. Of course we support dynamics and quantities in Toss almost from the start. But it is neither efficient enough nor mature enough. Let's start with vision. Lukasz Stafiniak suggested to use an algorithm called Condensation, see e.g. the attached paper. This algorithm is based on a population of samples for which a stochastic model of dynamics is known. One uses the model to choose where to look and resample - speaking very crudely. This way the condensation works - on a very high level - looks to me to be quite similar to the cma-es algorithm for minimizing functions - the one I want to use for selection of continuous moves. A good paper that also describes the difference to particle swarm optimization is attached, but the key point is again the same: we have a number of samples, this time all gaussian, which move to minimize the function. Ok - no dynamics model or adjusting to what is observed here - but the same idea: a numer of samples used to represent a distribution that all together give a nice model. Now - to track the dynamics in condensation one needs to have some model of dynamics already. If we don't have it but want to create one, we could use some methods from another paper Lukasz Stafiniak recently linked. They show how a multi-modal symbolic regression (MMRS, attached as well) can be used to derive a model from the training data. We would need to track and derive at the same time, but, except for the added computational cost which might be big, this seems to be doable - at least in principle. But MMRS internally again uses evolutional optimization methods, in some sense it is another layer on top, like a recursive call in a sense. This is another thing that made me think: maybe we need a probabilistic quantitative model of relational structures, and then we could build it all on top of this in a clear systematic way? About adding quantities: there is also an internal need in Toss for doing this in a better way. Let me just recall that we have already 12 cases in our main formula type, and another 9 in real_expr. At some point each of those things was needed, but it starts to be hard to use - and I cannot tell why And and Or are built over a list but Plus and Times are only binary. And we still lack min, max, sin, cos - some things that will be needed for dynamics. So we will need to rework this part, and I think we should first think and discuss and maybe we'll find a better universal model for all this stuff. One thing I see now, is that we could assume *every* relation in the structure to be quantitative, always. It is easy to include true and false, e.g. as true = +infty, false = -infty. Then and/or will be max/min, and real-valued functions will not be needed in the structure type any more - they'll be simply predicates. This also unifies formula and real_expr to one type and I think that it would directly make quite a few things easier in our code. But I don't want to make a small restructuring only - let's try to think a bit deeper and find the right model, for both quantities like colors or positions, Boolean values, and probabilities too. One thing to watch in this context is Stuart Russell's lecture about probabilistic relational structures. It will be streamed live from Paris, tomorrow 6pm Paris time, see here. http://colloquium.lip6.fr/ It is hard to tell what the lecture will be about exactly, but attached is a paper on BLOG, a probabilistic logic over relational structures developed by Russell. I suggest to read it before the lecture :). Best! Lukasz P.S. As to time planning - I think we will do a release quite soon, before we move to implement any ideas discussed in this thread. |
|
From: Lukasz S. <luk...@gm...> - 2013-01-18 09:52:15
|
On Fri, Jan 18, 2013 at 12:57 AM, Lukasz Kaiser <luk...@gm...> wrote: > Dear Thomas, > >> In your mini OCaml tutorial, you explain how to compile a project using >> ocamllex, menhir and js_of_ocaml using ocamlbuild but your explanations make >> the assumption that the files needed for js_of_ocaml are in >> /opt/local/lib/ocaml/site-lib. Unfortunately I installed js_of_ocaml using >> OPAM and don't know where it is installed (and don't want to because it may >> change if I switch to another version of ocaml/js_of_ocaml). > > indeed - we make some assumptions because it is very hard to > anticipate all possible ways of installing js_of_ocaml. If you are > under a POSIX system (e.g. Linux or Mac OS) then maybe it is > enough if you do "locate js_of_ocaml" in the terminal. Łukasz: This is not a principled solution... Thomas: Bear in mind that the tutorial is not intended to describe the best OCaml practices but rather to invite people to learn Toss and perhaps contribute to it. We have considered a better support for packaging but didn't have resources to pursue it yet. Regards. |
|
From: Lukasz K. <luk...@gm...> - 2013-01-17 23:58:17
|
Dear Thomas, > In your mini OCaml tutorial, you explain how to compile a project using > ocamllex, menhir and js_of_ocaml using ocamlbuild but your explanations make > the assumption that the files needed for js_of_ocaml are in > /opt/local/lib/ocaml/site-lib. Unfortunately I installed js_of_ocaml using > OPAM and don't know where it is installed (and don't want to because it may > change if I switch to another version of ocaml/js_of_ocaml). indeed - we make some assumptions because it is very hard to anticipate all possible ways of installing js_of_ocaml. If you are under a POSIX system (e.g. Linux or Mac OS) then maybe it is enough if you do "locate js_of_ocaml" in the terminal. (You must have locate installed, it often comes by default, but not always.) This should show you the path to js_of_ocaml on your system. A shorter option with locate is e.g. "locate pa_js.cmo", you can also search your system for the pa_js.cmo file in many other ways. I hope this helps to find your js_of_ocaml - I'd be happy to add a more general solution to the tutorial, but the OPAM websited so not seem to give any direct hints where the OPAM packages are placed, so I don't know how to do this for now. I still hope you will locate your packages without problems, do not hesitate to write if you need anything, Best regards! Lukasz Kaiser |
|
From: Thomas H. <tho...@gm...> - 2013-01-17 20:06:05
|
Hello, In your mini OCaml tutorial, you explain how to compile a project using ocamllex, menhir and js_of_ocaml using ocamlbuild but your explanations make the assumption that the files needed for js_of_ocaml are in /opt/local/lib/ocaml/site-lib. Unfortunately I installed js_of_ocaml using OPAM and don't know where it is installed (and don't want to because it may change if I switch to another version of ocaml/js_of_ocaml). How can I compile your mini tutorial with my installation of js_of_ocaml ? -- Thomas HUET |
|
From: Lukasz S. <luk...@gm...> - 2013-01-08 23:52:23
|
"A hybrid dynamical system is a mathematical model suitable for describing an extensive spectrum of multi-modal, time-series behaviors, ranging from bouncing balls to air traffic controllers. This paper describes multi-modal symbolic regression (MMSR): a learning algorithm to construct non-linear symbolic representations of discrete dynamical systems with continuous mappings from unlabeled, time-series data. MMSR consists of two subalgorithms---clustered symbolic regression, a method to simultaneously identify distinct behaviors while formulating their mathematical expressions, and transition modeling, an algorithm to infer symbolic inequalities that describe binary classification boundaries. These subalgorithms are combined to infer hybrid dynamical systems as a collection of apt, mathematical expressions. MMSR is evaluated on a collection of four synthetic data sets and outperforms other multi-modal machine learning approaches in both accuracy and interpretability, even in the presence of noise. Furthermore, the versatility of MMSR is demonstrated by identifying and inferring classical expressions of transistor modes from recorded measurements." (I haven't looked into it yet.) http://jmlr.csail.mit.edu/papers/v13/ly12a.html |
|
From: Lukasz S. <luk...@gm...> - 2013-01-03 10:42:26
|
I suggest we have a look at: http://www.robots.ox.ac.uk/~misard/condensation.html http://www.robots.ox.ac.uk/~misard/abstracts/thesis.html http://link.springer.com/article/10.1023%2FA%3A1008078328650 I got there from http://en.wikipedia.org/wiki/Video_tracking Happy New Year. "The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimodal, cannot represent simultaneous alternative hypotheses. The Condensation algorithm uses “factored sampling”, previously applied to the interpretation of static images, in which the probability distribution of possible interpretations is represented by a randomly generated set. Condensation uses learned dynamical models, together with visual observations, to propagate the random set over time. The result is highly robust tracking of agile motion. Notwithstanding the use of stochastic methods, the algorithm runs in near real-time." |
|
From: Lukasz K. <luk...@gm...> - 2012-11-16 14:47:52
|
At italkproject.org you can read more about it, they use the iCub robot to test their hypoteses. What I found interesting for Toss is that paper www.tech.plym.ac.uk/SoCCE/ITALK/documents/ITALKroadmap2010.pdf especially Section VI B and C (p.20,21, also attached). It discusses the relationship between action, social games and language, which I compare to the problem we have of integrating Term with the rest of Toss. Lukasz |
|
From: Lukasz S. <luk...@gm...> - 2012-11-13 22:45:03
|
http://jveness.info/publications/veness_phd_thesis_final.pdf "A B S T R A C T This thesis is split into two independent parts. The first is an investigation of some practical aspects of Marcus Hutter’s Universal Artificial Intelligence theory [29]. The main contributions are to show how a very general agent can be built and analysed using the mathematical tools of this theory. Before the work presented in this thesis, it was an open question as to whether this theory was of any relevance to reinforcement learning practitioners. This work suggests that it is indeed relevant and worthy of future investigation. The second part of this thesis looks at self-play learning in two player, deterministic, adversarial turn-based games. The main contribution is the introduction of a new technique for training the weights of a heuristic evaluation function from data collected by classical game tree search algorithms. This method is shown to outperform previous self-play training routines based on Temporal Difference learning when applied to the game of Chess. In particular, the main highlight was using this technique to construct a Chess program that learnt to play master level Chess by tuning a set of initially random weights from self play games." It is developed from the paper we looked at quite some time ago. |
|
From: Lukasz S. <luk...@gm...> - 2012-11-05 07:48:06
|
http://cs.jhu.edu/~jason/papers/#filardo-eisner-2012-iclp "Arithmetic circuits arise in the context of weighted logic programming languages, such as Datalog with aggregation, or Dyna. A weighted logic program defines a generalized arithmetic circuit—the weighted version of a proof forest, with nodes having arbitrary rather than boolean values. In this paper, we focus on finite circuits. We present a flexible algorithm for efficiently *querying* node values as they change under *updates* to the circuit's inputs. Unlike traditional algorithms, ours is agnostic about which nodes are tabled (materialized), and can vary smoothly between the traditional strategies of forward and backward chaining. Our algorithm is designed to admit future generalizations, including cyclic and infinite circuits and propagation of delta updates." |
|
From: Lukasz S. <luk...@gm...> - 2012-10-30 22:30:42
|
Hi, I recommend you to update Tuareg to the newest revision: http://forge.ocamlcore.org/scm/?group_id=43 |
|
From: Lukasz K. <luk...@gm...> - 2012-09-21 23:20:16
|
> Nullary (with regard to subterms) terms are translated as predicates > over a single element, unary terms as relations between the element > corresponding to the term and the element corresponding to the > subterm, arity N terms into arity N+1 relations. All supertypes are > translated as predicates / relations whose first argument is the same > element as the element generated for the whole term. That's the idea > behind translating terms to structures: a new element for each subterm > unless it is shared, but no new elements for supertypes. If you > recall, in the "formal" notation we represent terms by "f (supertypes > ; subterms)", and supertypes are of this form as well so can introduce > more subterms. You are absolutely right - I somehow misunderstood the previous mail very badly. Do you think we could get back formulas from the structures generated by terms relatively easily? That would be a good motivation, at least for me, to think about implementing this translation finally :). But I am still not entirely sure how this will help with formulas (even though now I think I start to see the point). Best! Lukasz |
|
From: Lukasz S. <luk...@gm...> - 2012-09-21 23:14:47
|
On Sat, Sep 22, 2012 at 12:54 AM, Lukasz Kaiser <luk...@gm...> wrote: > > I'm afraid that I do not fully understand - why are these quantified variants > of translating to structures, and why is that easier? I am surely in favour > of starting with the easier thing! Nullary (with regard to subterms) terms are translated as predicates over a single element, unary terms as relations between the element corresponding to the term and the element corresponding to the subterm, arity N terms into arity N+1 relations. All supertypes are translated as predicates / relations whose first argument is the same element as the element generated for the whole term. That's the idea behind translating terms to structures: a new element for each subterm unless it is shared, but no new elements for supertypes. If you recall, in the "formal" notation we represent terms by "f (supertypes ; subterms)", and supertypes are of this form as well so can introduce more subterms. |
27 messages has been excluded from this view by a project administrator.