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Prolog+CG is a Java implementation of Prolog with extensions implementing a subset of the Conceptual Graph (CG) theory of John Sowa. CGs are first-class datatypes on a par with terms. Object oriented extensions are also included.
This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package
...Calvo, Anindito Aditomo and Luiz Augusto Pizzato (2012), “Using Wikipedia and Conceptual Graph Structures to Generate Questions for Academic Writing Support”, IEEE Transactions on Learning Technologies, vol. 5, no. 3, pp. 251-263.
Asteroid has been merged with Scampi, to give rise to OScar.
Follow us on https://bitbucket.org/oscarlib/oscar/wiki/Home
Asteroid offers a powerful framework for developing constraint-based local search solution to combinatorial problems. This technique provides good scalability to real-world problems. It includes a library of standard constraints and invariants to declaratively define the problem you want to solve, and it also provides powerful search mechanisms.
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NaruGo is game AI project. Current targets are GO board game and Texas Holdem poker. It investigates Genetic programming to build game AI logic. Also EA/GP simulations for TSP, Graph layout and Prisoners Dilemma problem.
Game Toolbox is a C# assembly designed to facilitate the creation of games and game prototypes. It contains no graphics code, does not depend on XNA, and is Mono-compatible. It provides implementations of A*, GOAP, a genetic algorithm, and more.
An adaptive mini database learns algorithmic operations for data intensive algebraic computational methods within a pervasive computing graph. It also provides generic structures and algorithms as a data fabric.
RectaGraphTrace aims to assist in step-by-step visualization of graph search algorithms by displaying graphs and automating the creation and correction of graph traces such as those that a student would produce while manually executing a search.