In a multi-user, real-time, and situation-based learning environment, the availability of enough and appropriate situations is crucial for success. In order to improve effectivenes...
In this paper, we present the use of stochastic learning automata (SLA) in mutliagent robotics. In order to fully utilize and implement learning control algorithms in the control o...
Aly I. El-Osery, John Burge, Mohammad Jamshidi, An...
Researchers in the eld of Distributed Arti cial Intelligence (DAI) have been developing e cient mechanisms to coordinate the activities of multiple autonomous agents. The need for...
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...
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...