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The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners.
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The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
DUAPI (distributed unified agent programming interface) is a class library for creating and modelling the society of autonomous software agents. It also common to active objects and virtualization paradigm at all.
This is a fork of the JollyNinja Bot for Robocode. The project intends to document JollyNinja's source code, make it work in teams and provide a solid API to base other Bots on, especially TeamRobot based bots.
This project simulates a multi-agent system (swarm) behavior both graphically and not. The purpose of this project is to research the properties suggested in "stability analysis of swarms" V.Gazi & K.M.Passino. Using the vpython library for 3D modeling
"The gAIme" is the real time strategy where player can codeAI for his units using scripting language (LUA) or special logic editor. Play and survive in this bot's world!
Framework for modelling of Natural General Intelligence. This project aims at creation of open source AGI (Artificial General Intelligence) through modelling of natural thinking. See http://roland.pri.ee/bakalaureusetoo/ for theoretical details.