Backpropagation of errors is not only hard to justify from biological perspective but also it fails to solve problems requiring complex logic. A simpler algorithm based on generati...
Decentralized MDPs provide a powerful formal framework for planning in multi-agent systems, but the complexity of the model limits its usefulness. We study in this paper a class o...
Raphen Becker, Shlomo Zilberstein, Victor R. Lesse...
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
The paper deals with on-board planning for a satellite swarm via communication and negotiation. We aim at defining individual behaviours that result in a global behaviour that me...
Many-objective problems are difficult to solve using conventional multi-objective evolutionary algorithms (MOEAs) as these algorithms rely primarily on Pareto ranking to guide the ...