We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy but may behave differently due to position-dependent inputs. All...
Abstract. We present and evaluate in this paper a multi-agent approach for range image segmentation. The approach consists in using autonomous agents for the segmentation of a rang...
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
We describe a general mechanism for adaptation in multiagent systems in which agents modify their behavior based on their memory of past events. These behavior changes can be elic...
Decomposition has proved an effective strategy in planning, with one decomposition-based planner, SGPLAN, exhibiting strong performance in the last two IPCs. By decomposing planni...