Multiagent systems is an attractive problem solving approach that is becoming ever more feasible and popular in today’s world. It combines artificial intelligence (AI) and distr...
This paper investigates the adaptability of XCS in four different multiagent environments. The environments are realized in a simplified soccer game, and they include (1) singlea...
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
This paper proposes a very general max-margin learning framework for distance-based clustering. To this end, it formulates clustering as a high order energy minimization problem w...
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...