Search Results for "game"

How can we develop artificial intelligence that learns to make sense of complex environments? That learns from others, including humans, how to interact with the world? That learns transferable skills throughout its existence, and applies them to solve new, challenging problems? Project Malmo sets out to address these core research challenges, addressing them by integrating (deep) reinforcement learning, cognitive science, and many ideas from artificial intelligence. The Malmo platform...

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. Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit: http://search.maven.org/#search|ga|1|teachingbox FOR DEVELOPERS: 1) If you use Apache Maven, just add the following dependency to your pom.xml: <dependency> <groupId>org.sf.teachingbox</groupId> <artifactId>teachingbox-core</artifactId> <version>1.2.3</version> </dependency> 2) If you want to check out the most recent source-code: git clone https://git.code.sf.net/p/teachingbox/core teachingbox-core Documentation: https://sourceforge.net/p/teachingbox/documentation/HEAD/tree/trunk/manual/

This Java-application contains all required components to simulate a game of Ms. Pac-Man and let an agent learn intelligent playing behaviour using reinforcement learning and either Q-Learning or SARSA. The framework was developed by Luuk Bom and Ruud Henken, under supervision of Marco Wiering, Department of Artificial Intelligence, University of Groningen. It formed the basis of a bachelor's thesis titled "Using reinforcement learning with relative input to train Ms.

RL Poker is a study project Java implementation of an e-soft on-policy Monte Carlo Texas Hold'em poker reinforcement learning algoritm with a feedforward neural network and backpropagation. It provides a graphical interface to monitor game rounds.