Monte-Carlo Search Algorithms
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open in viewerWe have developed the Gomba Testing Framework, a new platform for the comparative evaluation of search algorithms in large adversarial game trees. Gomba is simple, fast, extensible, objective, and can scale to larger trees than previous frameworks have been able to test against. We have implemented and tested a variety of Monte-Carlo based search algorithms using the framework and have analyzed their performance in relation to known metrics in computer Go. Finally, we have taken several solutions to the infinitely-many-armed bandit problem and adapted them to tree search. We have tested these variants in both Gomba and computer Go, and have shown that they can be effective in both cases.
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Publisher
- Identifier
- E-project-042810-054003
- Advisor
- Year
- 2010
- Center
- Sponsor
- Date created
- 2010-04-28
- Location
- Budapest
- Resource type
- Major
- Rights statement
Relations
- In Collection:
Items
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Thumbnail | Title | Visibility | Embargo Release Date | Actions |
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djb_jns_mqp_report.pdf | Public | Download | ||
djb_jns_mqp_gomba_source.zip | Public | Download | ||
djb_jns_mqp_presentation.pdf | Public | Download |
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