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.
Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search : Tag: : Adversarial search - Artificial Intelligence and Machine Learning - Role of Game Playing in AI
Artificial Intelligence and Machine Learning
CS3491 4th Semester CSE/ECE Dept | 2021 Regulation | 4th Semester CSE/ECE Dept 2021 Regulation