—In this paper we apply Coevolutionary Temporal Difference Learning (CTDL), a hybrid of coevolutionary search and reinforcement learning proposed in our former study, to evolve s...
Abstract— This paper compares the use of temporal difference learning (TDL) versus co-evolutionary learning (CEL) for acquiring position evaluation functions for the game of Othe...
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Previous research on the use of coevolution to improve a baseline chess program demonstrated a performance rating of 2550 against Pocket Fritz 2.0 (PF2). A series of 12 games (6 wh...
David B. Fogel, Timothy J. Hays, Sarah L. Hahn, Ja...
While recently the strength of chess-playing programs has grown immensely, their capability of explaining in human understandable terms why some moves are good or bad has enjoyed l...
Aleksander Sadikov, Martin Mozina, Matej Guid, Jan...