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...
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Holland's Adaptation in Natural and Artificial Systems largely dealt with how systems, comprised of many self-interested entities, can and should adapt as a whole. This semin...
Robert E. Smith, Claudio Bonacina, Paul E. Kearney...
We propose in this paper a generic algorithm based on Ant Colony Optimization to solve multi-objective optimization problems. The proposed algorithm is parameterized by the number...
Recent studies [13, 18] have shown that clearing schemes are efficient multi-modal optimization methods. They efficiently reduce genetic drift which is the direct reason for prema...