An evolutionary reinforcement-learning algorithm, the operation of which was not associated with an optimality condition, was instantiated in an artificial organism. The algorithm ...
In this paper we describe an integrated multilevel learning approach to multiagent coalition formation in a real-time environment. In our domain, agents negotiate to form teams to...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
We consider the problem of learning to attain multiple goals in a dynamic environment, which is initially unknown. In addition, the environment may contain arbitrarily varying ele...
The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...