Open Source Java Artificial Intelligence Software - Page 17

CILib is a framework for developing Computational Intelligence software in swarm intelligence, evolutionary computing, neural networks, artificial immune systems, fuzzy logic and robotics.

CRML - Conflict Resolution Markup Language - http://www.equiforum.org - is an open source innitiative to develop an XML based Semantic Web ontology (RDF, OWL) for researchers interested in peace to create a standard way of collecting and sharing informa

Traditional Malaysian board game. Similar to Mancala. Implement NeuralNetwork (NN) agent, Min-Max, and Random move. System is based on Adam Cofer's Mancala system (2003). Also using Neuroph 2.5b by Zoran Servarac for NN. All code under GPLv3.

Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.

There are many tools available in market which will provide spell correction or grammer correction while making documents, but very few tools are available which are providing sentence completion according to previously entered text. But this all are providing sentence complition suggestion for sentences which are oftenly or regularly used by all people in same manner. But in reality style of writing changes person to person. While our aim is to provide a sentence suggestion tool which will give suggestion to complete the sentence according previously enterd data by the user. Output or suggestion for same sentence or word will change person to person according to previously entered data by that person. So, it will be very easy to type any document, sms, mail, chatting etc.

Constrainer is a Constraint Satisfaction Environment written in Java. It is currently being actively developed and supported as part of another project OpenL Tablets here on Sourceforge: http://sourceforge.net/projects/openl-tablets/?source=navbar

Contextor is a light-weight simple-to-use Java based library to help developers and researchers working with the general concept of a resource; as examples, resources can be text resources, web resources, images and videos.

Convince Me is a Java application for generating and analyzing arguments. Convince Me uses a connectionist model, called ECHO, to provide feedback on the coherence of the arguments entered into the application.

Cougar Squared is a new Java library for machine learning and data mining research, supporting research needs of the community. It is written by researchers for researchers. It extends the WEKA and YALE machine learning frameworks.

Since the method proposed in https://www.researchgate.net/publication/262599199_Unifying_Provenance_and_Debugging_for_Answer-Set_Programs?ev=prf_pub is based on meta-programming, it is possible to use existing state-of-the-art software systems that support well-founded and answer-set semantics, which allowed us to start developing this new tool by extending the one that exists related to a debugging approach: Spock, hence the name Cpt. Kirk. Furthermore and more importantly, one direction to explore is to use the technique of reification as described in "metaASP" to obtain the implicants via a saturation technique, and obtaining the prime implicants of provenance formulae by optimization and thus proper minimal justifications.

Harnessing the wisdom of the crowd to trade.

Optical Character Recognition (OCR) software.

Cunei is a data-driven machine translation system that builds dynamic, statistical models based on instances of known translations found in a corpus.

Cutting Problem solved by Genetic algorithms. The goal is to cut a rectangular plate of material into more smaller rectangles. The cuts must be rectangular and guillotinable.

This project is part of the "MRP" AI course held at the Dept. of computer science, Comenius University, Bratislava, Slovakia. The goal is a creation of a machine translation system (partly) specific for the Czech and Slovak languages only.

D-Cog (Declarative-Cognition) is a Java based framework for training software components (reusable, object-oriented, interface-driven components). Instead of programmed, software components are trained by example to get the expected results.

D.U.C.K (Determine segmentation of Unknown words by using Context Knowledge)is an NLP tool, which aims to find the correct segmentation for unknown words in written Hebrew. Statistics from different scopes will be used to determine the segmentation.

D3Kbot is a list handling chat bot for twitch.tv streamers The bot will allow chatters to join a waiting list to play on stream!! PLEASE READ THE WIKI vvvvvvvvvvvvvvvvvvvvvvvvv

Dataset Retrieval through Intelligent Agents (DARIA): is an Open Source project for facilitating the construction of ARFF data set files for use with WEKA or any such Machine Learning/Data Mining Software through the use of Intelligent Agents.

DBpedia has moved to GitHub: https://github.com/dbpedia/extraction-framework/wiki The mailing lists are still hosted by SourceForge. DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia and to link other datasets on the Web to Wikipedia data.

DBpedia Spotlight is a tool for annotating mentions of DBpedia resources in natural language text. The source code is now hosted on GitHub: https://github.com/dbpedia-spotlight

DCOPolis is a framework for comparing and deploying distributed decision processes in heterogeneous environments, including simulation in a virtual machine.

We propose the use of Differential Evolution algorithm for the weight adjustment of base classifiers used in weighted voting heterogeneous ensemble of classifier. Average Matthews Correlation Coefficient (MCC) score, calculated over 10-fold cross-validation, has been used as the measure of quality of an ensemble. DE/rand/1/bin algorithm has been utilised to maximize the average MCC score calculated using 10-fold cross-validation on training dataset. The voting weights of base classifiers are optimized for the heterogeneous ensemble of classifiers aiming to attain better generalization performances on testing datasets.

Some of the usual problems for Learning vector quantization (LVQ) based methods are that one cannot optimally guess about the number of prototypes required for initialization for multimodal data structures i.e.these algorithms are very sensitive to initialization of prototypes and one has to pre define the optimal number of prototypes before running the algorithm. If a prototype, for some reasons, is ‘outside’ the cluster which it should represent and if there are points of a different categories in between, then the other points act as a barrier and the prototype will not find its optimum position during training. Since the model complexity is not known in many cases, we avoid this problem by introducing a "Dynamic" version of LVQ. Dynamic-GRLVQ (DGRLVQ), which adapts the model complexity to the given problem during training by adding or removing prototypes dynamically/realtime one by one for each category until satisfactory classification results are achieved.

A multi-agent architecture for building interactive dramas. It uses the Jason's BDI engine, being the Jason's agent-oriented programming language utilized for performing the drama management and for authoring behaviors for the characters.