Thinknowlogy is grammar-based software designed to utilize the logic contained within grammar in order to create intelligence through a natural language, which is demonstrated by programming in a natural language, reasoning in a natural language (drawing conclusions, making assumptions (with a self-adjusting level of uncertainty), asking questions (about gaps in the knowledge), and detecting conflicts), and intelligent answering of "is" questions, providing alternative answers as well.
PEXESO Evolutionary Methods Library is the library of Evolutionary Optimization Methods for Real Domains. It is based on the original Object Oriented Algorithmic model that consists of the multi- operators technology (currently it supports 13 operator types) and "open policy" on the selection strategy (currently 4 selection strategy types). Using this method you have a possibility to compose your own optimization method using some combination of operators and selection strategies, or you can use one of 3 precomposed algorithms. It is provided with several examples and comprehensive HTML documentation.
(Multi-Agent) Transport Planner is a dynamic single agent transport planner for vehicle routing problems and dial-a-ride problems. These problems occur in every public transport and transportation company, but although some older algorithms can be found in the literature, a good implementation has never been published. It uses a (very quick) standard insertion technique to insert orders one by one into a set of routes.
The Artificial Knowledge Interface for Reasoning Applications (AKIRA) project aims to create a C++ development framework to build cognitive architectures and complex artificial intelligent agents featuring KQML, fuzzy logic, neural networks, fuzzy cognitive maps, and DIPRA. DIPRA is a distributed version of the BDI (Belief Desire Intention) goal oriented model.
lazar (Lazy-Structure-Activity Relationships) is a tool for the prediction of toxic activities of chemical structures. lazar derives predictions from databases with experimental toxicity data. It searches in these databases for compounds with similar structures and calculates the prediction from their measured activities.
RegMAS (Regional Multi Agent Simulator) is a spatially explicit multi-agent model framework, designed for long-term simulations of effects of government policies over agricultural systems (e.g. farm sizes, incomes, land use). RegMAS uses a profit-maximization algorithm to derive farmers' behaviors. Using RegMAS, researchers can write regional-specific models, adapting the pool of activities and resources to their specific region.