Name
Abstract | ||
|---|---|---|
In this paper we present a full-fledged player for general games with incomplete information specified in the game description language GDL-II. To deal with uncertainty we introduce a method that operates on partial belief states, which correspond to a subset of the set of states building a full belief state. To search for a partial belief state we present depth-first and Monte-Carlo methods. All can be combined with any traditional general game player, e.g., using minimax or UCT search. Our general game player is shown to be effective in a number of benchmarks and the UCT variant compares positively with the one-and-only winner of an incomplete information track at an international general game playing competition. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33347-7_3 | KI |
Keywords | Field | DocType |
full-fledged player,uct search,general game,traditional general game player,incomplete information,uct variant,partial belief state,general game player,game description language gdl-ii,full belief state,international general game | Combinatorial game theory,Mathematical economics,Strategy,Repeated game,Artificial intelligence,General game playing,Sequential game,Bayesian game,Information set,Mathematics,Extensive-form game | Conference |
Citations | PageRank | References |
10 | 0.66 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefan Edelkamp | 1 | 1557 | 125.46 |
| Tim Federholzner | 2 | 10 | 0.66 |
| Peter Kissmann | 3 | 181 | 13.93 |