We present an anytime multiagent learning approach to satisfy any given optimality criterion in repeated game self-play. Our approach is opposed to classical learning approaches fo...
Abstract. We consider network congestion games in which a finite number of non-cooperative users select paths. The aim is to mitigate the inefficiency caused by the selfish users...
Dimitris Fotakis, George Karakostas, Stavros G. Ko...
This paper introduces a new model, i.e. state-coupled replicator dynamics, expanding the link between evolutionary game theory and multiagent reinforcement learning to multistate ...
Two-way alternating automata were introduced by Vardi in order to study the satisfiability problem for the modal µ-calculus extended with backwards modalities. In this paper, we ...
We propose a simple theory of expressions which is intended to be used as a foundational syntactic structure for the Natural Framework (NF). We define expression formally and give...