Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...
Effective coordination of robots, agents and people promises to improve the safety, robustness and quality with which shared goals are achieved by harnessing the highly heterogene...
Paul Scerri, David V. Pynadath, W. Lewis Johnson, ...
This paper describes the integration of perceptual guidelines from human vision with an AI-based mixed-initiative search strategy. The result is a visualization assistant called Vi...
Christopher G. Healey, Sarat Kocherlakota, Vivek R...
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...
Research in collective robotics is motivated mainly by the possibility of achieving an efficient solution to multi-objective navigation tasks when multiple robots are employed, in...
Renato Reder Cazangi, Fernando J. Von Zuben, Maur&...