A fundamental difficulty faced by groups of agents that work together is how to efficiently coordinate their efforts. This paper presents techniques that allow heterogeneous agent...
Abstract. Although several approaches to the semantics of agent communication have been proposed, none of them is really suitable for dealing with agent autonomy, which is a decisi...
Matthias Nickles, Michael Rovatsos, Gerhard Wei&sz...
The missing of an appropriate semantics of agent communication languages is one of the most challenging issues of contemporary AI. Although several approaches to this problem exis...
Matthias Nickles, Michael Rovatsos, Gerhard Wei&sz...
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
Procedural representations of control policies have two advantages when facing the scale-up problem in learning tasks. First they are implicit, with potential for inductive genera...