Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search

Role of Game Playing in AI

Adversarial search - Artificial Intelligence and Machine Learning

There were two reasons that games appeared to be a good domain in which to explore machine intelligence-They provide a structured task in which it is very easy to measure success or failure.

Role of Game Playing in Al

There were two reasons that games appeared to be a good domain in which to explore machine intelligence -

i) They provide a structured task in which it is very easy to measure success or failure.

ii) They did not obviously require large amounts of knowledge. They were thought to be solvable by straightforward search from the starting state to a winning position.

The first of these reasons remains valid and accounts for continued interest in the area of game playing by machine. Unfortunately, the second is not true for any but the simplest games. For example, consider chess, playing it on computer has to face problems of combinational explosion of solutions due to the following reasons

The average branching factor is around 35.

In an average game, each player might make 50 moves.

So in order to examine the complete game tree, one would need to examine 35100 positions.

In addition to the above two reasons there are some more reasons, why game-playing occupies a pivotal role in AI are -

i) The rules of games are very limited. Hence, extensive amounts of domain-specific knowledge are seldom needed.

ii) Many human experts exist to assist in the developing of the programs. Hence, the problem of shortage of human experts does not arise.

iii) For the human expert, it is easy to explain the rationale for a move unlike other domains.

iv) Games picturize real life situations in a constricted fashion. The logical reasoning ability of the human in a normal condition and under stress is clearly exhibited in game-playing. Moreover game-playing permits one to simulate real-life situations.

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Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search



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Artificial Intelligence and Machine Learning

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