Game Playing AI in Action: Mastering Game Strategies with Minimax and Beyond !!
Abstract : Game Playing is an important domain of artificial intelligence. Games don’t require much knowledge; the only knowledge we need to provide is the rules, legal moves and the conditions of winning or losing the game. Both players try to win the game. So, both of them try to make the best move possible at each turn. Searching techniques like BFS(Breadth First Search) are not accurate for this as the branching factor is very high, so searching will take a lot of time. So, we need another search procedures that improve – Generate procedure so that only good moves are generated. Test procedure so that the best move can be explored first. The most common search technique in game playing is Minimax search procedure. It is depthfirst depth-limited search procedure. It is used for games like chess and tic-tac-toe. The minimax algorithm is a recursive algorithm used in game theory to find the best move for a player in a game. It's based on the assumption that the other p