Name
Abstract | ||
|---|---|---|
Chess programs can differ in depth of search or in the evaluation function applied to leaf nodes or both. Over the past 10 years, the notion that the principal way to strengthen a chess program is to improve its depth of search has held sway. Improving depth of search undoubtedly does improve a program's strength. However, projections of potential gain have time and again been found to overestimate the actual gain. |
Year | DOI | Venue |
|---|---|---|
1990 | 10.1016/0004-3702(90)90067-A | Artif. Intell. |
Keywords | Field | DocType |
performance potential,chess program | Data science,Computer science,Evaluation function,Software,Artificial intelligence,World championship,Machine learning | Journal |
Volume | Issue | ISSN |
43 | 1 | 0004-3702 |
Citations | PageRank | References |
21 | 4.66 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hans J. Berliner | 1 | 254 | 252.67 |
| Gordon Goetsch | 2 | 22 | 5.65 |
| Murray S. Campbell | 3 | 103 | 25.42 |
| Carl Ebeling | 4 | 1405 | 185.32 |