Abstract. Constraint Satisfaction has been widely used to model static combinatorial problems. However, many AI problems are dynamic and take place in a distributed environment, i....
Recent technological advances in imaging industry have lead to the production of imaging systems with high density pixel sensors. However, their long exposure times limit their app...
Maria E. Angelopoulou, Christos-Savvas Bouganis, P...
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...
Meta-level control manages the allocation of limited resources to deliberative actions. This paper discusses efforts in adding meta-level control capabilities to a Markov Decision...
In this paper we propose interaction-driven Markov games (IDMGs), a new model for multiagent decision making under uncertainty. IDMGs aim at describing multiagent decision problem...