Many multiagent problems comprise subtasks which can be considered as reinforcement learning (RL) problems. In addition to classical temporal difference methods, evolutionary algo...
Jan Hendrik Metzen, Mark Edgington, Yohannes Kassa...
This paper describes how multiagent systems can be used to achieve robust software, one of the major goals of software engineering. The paper first positions itself within the sof...
Michael N. Huhns, Vance T. Holderfield, Rosa Laura...
How an internal observer, that is not given any a priori knowledge or interpretation of what its sensors receives, learn to imitate seems a formidable issue from a viewpoint of a c...
SkeletonAgent is an agent framework whose main feature is to integrate different artificial intelligent skills, like planning or learning, to obtain new behaviours in a multi-agen...
The detection of attacks against computer networks is becoming a harder problem to solve in the field of network security. The dexterity of the attackers, the developing technolog...