Name
Abstract | ||
|---|---|---|
In this paper, we introduce a universal game playing agent that is able to successfully play a wide variety of video games. It combines the strengths of Monte Carlo tree search with conventional heuristic search into a single hybrid search agent, which is able to select the appropriate strategy based on its observations about the game dynamics. In particular, the agent learns a knowledge base whic... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCIAIG.2017.2722235 | IEEE Transactions on Games |
Keywords | DocType | Volume |
Games,Monte Carlo methods,Search problems,Knowledge based systems,Stochastic processes,Aerospace electronics | Journal | 10 |
Issue | ISSN | Citations |
1 | 2475-1502 | 7 |
PageRank | References | Authors |
0.52 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tobias Joppen | 1 | 7 | 0.52 |
| Miriam Ulrike Moneke | 2 | 7 | 0.52 |
| Nils Schröder | 3 | 7 | 0.52 |
| Christian Wirth | 4 | 19 | 1.91 |
| Johannes Fürnkranz | 5 | 2476 | 222.90 |