Recognizing commonly used data structures and algorithms is a key activity in reverse engineering. Systems developed to automate this recognition process have been isolated, stand...
Multi-case-base reasoning (MCBR) extends case-based reasoning to draw on multiple case bases that may address somewhat different tasks. In MCBR, an agent selectively supplements i...
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
There has been a growing interest in designing multi-agent based interactive dramas. A key research challenge faced in the design of these systems is to support open-ended user in...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...