Abstract. Most of multi-agent reinforcement learning algorithms aim to converge to a Nash equilibrium, but a Nash equilibrium does not necessarily mean a desirable result. On the o...
Abstract. A new approach to teaching the skills used by health professionals during hands-on (palpation-based) examinations and procedures is reported, where students practice indi...
We consider imperfect-information parity games in which strategies rely on observations that provide imperfect information about the history of a play. To solve such games, i.e., t...
Perfect Information Monte Carlo (PIMC) search is a practical technique for playing imperfect information games that are too large to be optimally solved. Although PIMC search has ...
Jeffrey Richard Long, Nathan R. Sturtevant, Michae...
Obtaining labeled data is a significant obstacle for many NLP tasks. Recently, online games have been proposed as a new way of obtaining labeled data; games attract users by being...
David Vickrey, Aaron Bronzan, William Choi, Aman K...