We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
A general game player automatically learns to play arbitrary new games solely by being told their rules. For this purpose games are specified in the game description language GDL...
We study a simple continuous-time multiagent system related to Krause's model of opinion dynamics: each agent holds a real value, and this value is continuously attracted by e...
Vincent D. Blondel, Julien M. Hendrickx, John N. T...
We present a new approach to distributed problem solving based on high-level program execution. While this technique has proven itself for single-agent systems based on the Golog ...
We present the logic CTL.STIT, which is the join of the logic CTL with a multi-agent strategic stit-logic variant. CTL.STIT subsumes ATL, and adds expressivity to it that we claim...