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Search for games in AI

Posted on December 6, 2021December 6, 2021 By christo No Comments on Search for games in AI

There are following Search for games in AI used

Game Problem Formulation

  • A game with 2 players (MAX and MIN, MAX moves first, turn-taking) can be defined as a search problem with:
    • initial state: board position
    • player: player to move
    • successor function: a list of legal (move, state) pairs
    • goal test: whether the game is over – terminal states
    • utility function: gives a numeric value for the terminal states (win, loss, draw)
  • Game tree = initial state + legal moves

Optimal Strategies

  • MAX must find a contingent strategy, specifying MAX’s move in:
    • the initial state
    • the states resulting from every possible response by MIN
  • E.g., 2-ply game (the tree is one move deep, consisting of two half moves, each of which is called a ply):
Optimal Strategies
Optimal Strategies

Minimax Value

  • Perfect play for deterministic game, assume both players play optimally
  • Idea: choose move to position with highest minimax value = best achievable payoff against best play

A Partial Game Tree for Tic-Tac-Toe

A Partial Game Tree for Tic-Tac-Toe
A Partial Game Tree for Tic-Tac-Toe

Artificial intelligence

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