Reinforcement learning can provide a robust and natural means for agents to learn how to coordinate their action choices in multiagent systems. We examine some of the factors that...
Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
Effective norms, emerging from sustained individual interactions over time, can complement societal rules and significantly enhance performance of individual agents and agent soci...
The development of the World Wide Web has changed the way we think about information. Information on the web is distributed, updates are made asynchronously and resources come onli...
One of the greatest challenges in the design of realistic Artificial Intelligence (AI) in computer games is agent movement. Pathfinding strategies are usually employed as the core...