Abstract--Fingerprinting operators generate functional signatures of game players and are useful for their automated analysis independent of representation or encoding. The theory ...
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
In this paper we explore some of the connections between cooperative game theory and the utility maximization framework for routing and flow control in networks. Central to both a...
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Abstract--This article deals with the issue of concept learning and tries to have a game theoretic view over the process of cooperative concept learning among agents in a multi-age...