Abstract. Most existing evolutionary approaches to multiobjective optimization aim at finding an appropriate set of compromise solutions, ideally a subset of the Pareto-optimal se...
Johannes Bader, Dimo Brockhoff, Samuel Welten, Eck...
One of the most challenging aspects of reasoning, planning, and acting in a multi-agent domain is reasoning about what the agents know about the knowledge of their fellows, and to...
Chitta Baral, Gregory Gelfond, Tran Cao Son, Enric...
In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
Web prefetching mechanisms have been proposed to benefit web users by hiding the download latencies. Nevertheless, to the knowledge of the authors, there is no attempt to compare...
Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in rec...