Utveckling av minimax-baserad agent för strategispelet Stratego
(2006)Computer Science
- Abstract
- Stratego is a boardgame not very different from chess, that contains hidden information. Because of this, existing programs play at beginner level. The purpose of this thesis is to adjust a minimax algorithm so that it passes the demands of Stratego, and then build a Stratego agent around it. Tests with existing minimax algorithms leads to the development p-e-minimax. This algorithm uses two different values in its nodes to simulate the different information available to the agent and its opponent. The name of the agent constructed around p-e-minimax is Perspecto. This agent uses a hybrid architecture were a simple strategic search is used in paralell with p-e-minimax. The agent also uses a psychlolgical model to handle the game of the... (More)
- Stratego is a boardgame not very different from chess, that contains hidden information. Because of this, existing programs play at beginner level. The purpose of this thesis is to adjust a minimax algorithm so that it passes the demands of Stratego, and then build a Stratego agent around it. Tests with existing minimax algorithms leads to the development p-e-minimax. This algorithm uses two different values in its nodes to simulate the different information available to the agent and its opponent. The name of the agent constructed around p-e-minimax is Perspecto. This agent uses a hybrid architecture were a simple strategic search is used in paralell with p-e-minimax. The agent also uses a psychlolgical model to handle the game of the hidden pieces better.
Perspecto defeats a commercial program but loses to a human player after an even game. This and the following tests shows that a more advanced strategic search and a more unpredictable psychological model is needed for Perspecto to have a chance aganist a skilled human player. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/1326298
- author
- Stengård, Karl
- supervisor
- organization
- year
- 2006
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- numerical analysis, Computer science, hybrid architeture, hidden information, minimax algorithm, minimax-based agent, systems, control, Datalogi, numerisk analys, system, kontroll
- language
- Swedish
- id
- 1326298
- date added to LUP
- 2006-02-17 00:00:00
- date last changed
- 2009-04-20 11:17:40
@misc{1326298, abstract = {{Stratego is a boardgame not very different from chess, that contains hidden information. Because of this, existing programs play at beginner level. The purpose of this thesis is to adjust a minimax algorithm so that it passes the demands of Stratego, and then build a Stratego agent around it. Tests with existing minimax algorithms leads to the development p-e-minimax. This algorithm uses two different values in its nodes to simulate the different information available to the agent and its opponent. The name of the agent constructed around p-e-minimax is Perspecto. This agent uses a hybrid architecture were a simple strategic search is used in paralell with p-e-minimax. The agent also uses a psychlolgical model to handle the game of the hidden pieces better. Perspecto defeats a commercial program but loses to a human player after an even game. This and the following tests shows that a more advanced strategic search and a more unpredictable psychological model is needed for Perspecto to have a chance aganist a skilled human player.}}, author = {{Stengård, Karl}}, language = {{swe}}, note = {{Student Paper}}, title = {{Utveckling av minimax-baserad agent för strategispelet Stratego}}, year = {{2006}}, }