Learning belief distributions for game moves
US7647289B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 2, 2006 |
| Grant date | Jan 12, 2010 |
| Priority date | — |
| Expiry date | Mar 25, 2027 |
Classification
- Technology area (CPC A)Human Necessities
- CPC primaryA63F3/04
- WIPO fieldFurniture, games
- WIPO sectorOther fields
Abstract
We describe an apparatus for learning to predict moves in games such as chess, Go and the like, from historical game records. We obtain a probability distribution over legal moves in a given board configuration. This enables us to provide an automated game playing system, a training tool for players and a move selector/sorter for input to a game tree search system. We use a pattern extraction system to select patterns from historical game records. Our learning algorithm learns a distribution over the values of a move given a board position based on local pattern context. In another embodiment we use an Independent Bernoulli model whereby we assume each moved is played independently of other available moves.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.