Difference between revisions of "Batch Learning for Poker"
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This project is aimed at determination an efficient policy to play Poker Limit Hold`em Heads up. Subdivided in three major areas: | This project is aimed at determination an efficient policy to play Poker Limit Hold`em Heads up. Subdivided in three major areas: | ||
− | 1- Analysis of rules of poker and player strategies. | + | 1- Analysis of rules of poker and player strategies. |
2- Feature Extraction: Given the fact that number of possible states are quite large (10E14). A FS approach is necessary. | 2- Feature Extraction: Given the fact that number of possible states are quite large (10E14). A FS approach is necessary. | ||
3- Fitted Q-Iteration to determinate the policy using Extremely Randomized Trees. | 3- Fitted Q-Iteration to determinate the policy using Extremely Randomized Trees. |
Revision as of 13:22, 15 May 2010
MRT: Batch Learning for Poker
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Coordinator: | MarcelloRestelli (restelli@elet.polimi.it) |
Tutor: | |
Collaborator: | |
Students: | RafaelVilella (rafaelcarioca51@gmail.com) |
Research Area: | Machine Learning |
Research Topic: | |
Start: | 2010/03/01 |
End: | In progresswarning.pngThe date "In progress" was not understood. |
Status: | Active |
Type: | Thesis |
Contents
Project short description
This project is aimed at determination an efficient policy to play Poker Limit Hold`em Heads up. Subdivided in three major areas:
1- Analysis of rules of poker and player strategies.
2- Feature Extraction: Given the fact that number of possible states are quite large (10E14). A FS approach is necessary. 3- Fitted Q-Iteration to determinate the policy using Extremely Randomized Trees.
Dates
Start date: 2010/03/01
End date: Still in progress
Project head(s)
M.Restelli - User:MarcelloRestelli
Students currently working on the project
Rafael Domingues Santos Vilella - User:RafaelVilella
Laboratory work and risk analysis
This project is related to software developing so there are no dangerous activities