Advanced

Utveckling av minimax-baserad agent för strategispelet Stratego

Stengård, Karl (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:
author
Stengård, Karl
supervisor
organization
year
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
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},
  keyword      = {numerical analysis,Computer science,hybrid architeture,hidden information,minimax algorithm,minimax-based agent,systems,control,Datalogi,numerisk analys,system,kontroll},
  language     = {swe},
  note         = {Student Paper},
  title        = {Utveckling av minimax-baserad agent för strategispelet Stratego},
  year         = {2006},
}