Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
In online, dynamic environments, the services requested by consumers may not be readily served by the providers. This requires the service consumers and providers to negotiate the...
The problem of managing the evolution of complex and large software systems is well known. Evolution implies reuse and modification of existing software artifacts, and this means t...
Abstract. We present a method to improve the positive examples selection by teaching agents in a multi-agent system in which a team of agent peers teach concepts to a learning agen...
XCS is a learning classifier system that combines a reinforcement learning scheme with evolutionary algorithms to evolve rule sets on-line by means of the interaction with an envi...
Sergio Morales-Ortigosa, Albert Orriols-Puig, Este...