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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 45678 (19)
- University: Sharif University of Technology
- Department: Computer Engineering
- Advisor(s): Ghodsi, Mohammad
- Abstract:
- In recent years, game theory passed from areas of economics and socials to other fields such as computational biology and bioinformatics. Several evolutionary games and cooperative games have been defined to predict the behavior of nonrational agents in interaction situations arising from computational biology.One of the these main applications is using Shapley value. Shapley value allocates a fair value to each player, in games that each coalition has a profit.But in many cases the computation of Shapley value is #P-complete. Thus,the goal is to optimally find Shapley value or to approximate it in each game.Another option is Banzhaf index.One of the essential games on genes is Pathway game. In this game with some multi-knockout experiments, we want to find the influence of each gene in the result of the experiences. Due to the costly nature of the test, the objective is to minimize the number of experiments. We model pathway game in four levels of complexity and analyse each model for finding the Shapley value and the Banzhaf index of each gene with minimum experiences. We give optimal algorithms for each model, and prove a hardness for the third model
- Keywords:
- Computational Biology ; Algorithmic Game Theory ; Cooperative Game Theory ; Shaply Value ; Banzhaf Index ; Group Testing
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