We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents operating in multi-agent environments. We use the...
We develop a revealed-preferencetheory for multiple agents. Some features of our construction, which draws heavily on Jeffrey's utility theory and on formal constructions by D...
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...
We propose a new set of criteria for learning algorithms in multi-agent systems, one that is more stringent and (we argue) better justified than previous proposed criteria. Our cr...
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...