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...
In this paper, we report on an interactive system and the results ofa formal user study that was carried out with the aim of comparing two approaches to estimating users' int...
Boris Brandherm, Helmut Prendinger, Mitsuru Ishizu...
Many applications of networks of agents, including mobile sensor networks, unmanned air vehicles, autonomous underwater vehicles, involve 100s of agents acting collaboratively und...
Janusz Marecki, Tapana Gupta, Pradeep Varakantham,...
Multi-agent systems benefit greatly from an organization design that guides agents in determining when to communicate, how often, with whom, with what priority, and so on. However...
Huzaifa Zafar, Victor R. Lesser, Daniel D. Corkill...
Multiple-dimensional, i.e., polyadic, data exist in many applications, such as personalized recommendation and multipledimensional data summarization. Analyzing all the dimensions...