In many AI settings an agent is comprised of both actionplanning and action-execution components. We examine the relationship between the precision of the execution component, the...
Video games provide a rich testbed for artificial intelligence methods. In particular, creating automated opponents that perform well in strategy games is a difficult task. For in...
Games are used to evaluate and advance Multiagent and Artificial Intelligence techniques. Most of these games are deterministic with perfect information (e.g. Chess and Checkers)....
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
Verification of multi-agent programs is a key problem in agent research and development. This paper focuses on multi-agent programs that consist of a finite set of BDI-based agent...
In this paper we study, for the first time explicitly, the implications of endowing an interested party (i.e. a teacher) with the ability to modify the underlying dynamics of the ...
Zinovi Rabinovich, Lachlan Dufton, Kate Larson, Ni...
In systems of autonomous self-interested agents, in which agents' neighbourhoods are defined by their connections to others, cooperation can arise through observation of the ...
Experimental analysis of networks of cooperative learning agents (to verify certain properties such as the system's stability) has been commonly used due to the complexity of...
We demonstrate an approach for collision- and oscillationfree navigation of multiple robots or virtual agents amongst each other. Each entity acts independently and uses only both...
We introduce a novel case study in which a group of miniaturized robots screen an environment for undesirable agents, and destroy them. Because miniaturized robots are usually end...