Effective search control is one of the key components of any successful simulation-based game-playing program. In General Game Playing (GGP), learning of useful search-control knowledge is a particularly challenging task because it must be done in real-time during online play. In here we describe the search-control techniques used in the 2010 version of the GGP agent CadiaPlayer, and show how they have evolved over the years to become increasingly effective and robust across a wide range of games. In particular, we present a new combined search-control scheme (RAVE/MAST/FAST) for biasing action selection. The scheme proves quite effective on a wide range of games including chess-like games, which have up until now proved quite challenging for simulation-based GGP agents.
Bibliographical notePublisher Copyright:
© 2010, Springer-Verlag.
- General game playing
- Monte Carlo Tree Search
- Search control