EO is a template-based, ANSI-C++ evolutionary computation library that helps you to write your own stochastic optimization algorithms quickly. Evolutionary algorithms form a family of algorithms inspired by the theory of evolution, and solve various problems. They evolve a set of solutions to a given problem in order to produce the best results. These are stochastic algorithms because they iteratively use random processes. The vast majority of these methods are used to solve optimization problems, and may be also called "metaheuristics". They are also ranked among computational intelligence methods, a domain close to artificial intelligence. With the help of EO, you can easily design evolutionary algorithms that will find solutions to virtually all kind of hard optimization problems, from continuous to combinatorial ones.
HyperGraphDB is a general purpose, extensible, portable, distributed, embeddable data storage mechanism. Designed specifically for artificial intelligence and semantic web projects, it can also be used as an embedded object-oriented database for projects of all sizes. It is a Java-based product built on top of the Berkeley DB storage library. It can be used as a single in-process database bound to a location on the local disk or within a "cloud" of networked database instances communicating and sharing data in a P2P (peer-to-peer) fashion. Key features include storage of generalized hypergraphs, an open, extensible type system, basic query system and graph traversal algorithms, out-of-the-box support for Java object storage, thread-safe transactions, and a P2P framework for data distribution.
JEFF is an explanation facility framework written in Java. Explanation facilities date from the era of expert systems (ES), where they were used in order to provide an explanation about the inference process. The explanation they provided was supposed to clarify how the ES reached its conclusions or why it asked some question during fact acquisition. Nowadays, traditional ES development environments ("shells") have been replaced by rule engines (RE) and business rule management systems (BRMS), which seem to lack explanation facility functionality. JEFF was created in order to remedy this.
AceWiki is a semantic wiki that is powerful and at the same time easy to use. Making use of the controlled natural language ACE, the formal statements of the wiki are shown in a way that looks like natural English. In order to help the users to write correct ACE sentences, AceWiki provides a predictive editor.
Encog is an advanced neural network and bot programming library. It can be used independently either to create neural networks or HTTP bot programs. It also includes classes that combine these two advanced features. It contains classes for Feedforward Neural Networks, Hopfield Neural Networks, and self organizing maps. Training can be accomplished using back-propagation, simulated annealing, and genetic optimization. Additional classes are provided for pruning neural networks. Encog also includes advanced HTTP bot programming features. A multi-threaded spider that can store its workload either in memory on a database is provided. HTML parsing is provided, as well as advanced form and cookie handling.
tinyMAS is a multiagent platform that provides base concepts (such as kernel, message, yellow pages, white pages, and transport service) and extended concepts (such as environment, influence, and perception). It aims to provide an easy-to-understand and and easy-to-use platform dedicated for multiagent engineer/research courses. TinyMAS is no longer under development. A large amount of its source code has been merged into the Janus platform.
PED is a dialogue management system that uses a probabilistic nested belief model to choose dialogue strategies. The dialogue system designer need only supply a set of plan rules to PED as a dialogue grammar with preconditions. Using this grammar, PED constructs game trees (like the one below) to represent the outcomes of the dialogue, so that a dialogue strategy can be chosen for the current turn in the dialogue. PED automatically maintains a belief model by a belief revision process that uses the observed acts in the dialogue. The game tree is evaluated in the context of this belief model. PED is efficient because it uses probabilistic estimates of belief rather than a plain logical belief model.
Reasonable Python is a Python module which adds logic programming constructs borrowed from F-Logic. It's build upon the Flora-2 and XSB engines and uses ZODB for permanent knowledgebase storage. Usage possibilities include knowledge bases, ontology management and semantic web applications.