Learning to Take Concurrent Actions

Khashayar Rohanimanesh, Sridhar Mahadevan

Abstract: We investigate a general semi-Markov Decision Process (SMDP) framework for modeling concurrent decision making, where agents learn optimal plans over concurrent temporally extended actions. We introduce three types of parallel termination schemes { all, any and continue { and theoretically and experimentally compare them.