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...
Knowledge flow in interdisciplinary teams has become of particular interest as research and alliances cross traditional disciplinary boundaries, and as computing is applied in any...
A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...
Real world multiagent coordination problems are important issues for reinforcement learning techniques. In general, these problems are partially observable and this characteristic ...
Generating interest in specialized areas of Computer Science (CS) is one of the goals of the department of Computer and Information Science at Spelman College as with most departm...