Multi-agent teamwork is critical in a large number of agent applications, including training, education, virtual enterprises and collective robotics. The complex interactions of ag...
Ranjit Nair, Milind Tambe, Stacy Marsella, Taylor ...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
There is growing interest in multi-robot frequency-based patrolling, in which a team of robots optimizes its frequency of point visits, for every point in a target work area. In p...
Recent scaling up of decentralized partially observable Markov decision process (DEC-POMDP) solvers towards realistic applications is mainly due to approximate methods. Of this fa...
Endowing agents with “social rationality” [10, 12, 11] can aid overall efficiency in tasks where cooperation is beneficial to system level performance. However it is difficult...