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

Types of Games

Adversarial search - Artificial Intelligence and Machine Learning

Players must choose their strategies simultaneously, neither knowing what the other player is going to do.

Types of Games

1. Based on chance

i) Deterministic (not involving chance)

For example -

Chess, Checkers, Tic-tac-toe

ii) Non-deterministic (can involve chance)

For example

Backgammon, Monopoly.

2. Based on information

i) Perfect information -

Here all moves of all players are known to everyone.

For example -

Chess, Checker, Tic-tac-toe.

ii) Imperfect information -

Here all moves are not known to everyone.

For example:

Bridge, Pocker, Scrabble.

3. General zero-sum games

Players must choose their strategies simultaneously, neither knowing what the other player is going to do.

For example-

If you play a single game of chess with someone, one person will lose and one person will win. The win (+1) added to the loss (−.1) equals zero.

4. Constant-sum game

Here the algebraic sum of the outcomes are always constant, though not necessarily zero.

It is strategically equivalent to zero-sum games.

5. Non-zero-sum game

Here the algebraic sum of the outcomes are not constant. In these of the payoffs are not the same for all outcomes.

They are not always completely solvable but provide insights into important areas of inter-dependent choice.

In these games, one player's losses do not always equal another player's gains.

The non-zero-sum games are of two types: -

i) Negative sum games (Competitive) -

Here nobody really wins, rather everybody loses.

Example - A war or a strike.

ii) Positive sum games (Co-operative) -

Here all players have one goal that they contribute together.

Example - An educational game, building blocks, or a science exhibit.

6. N-person game

It involves more than two players.

Analysis of such games is more complex than zero-sum games.

Conflicts of interest are less obvious.

Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search : Tag: : Adversarial search - Artificial Intelligence and Machine Learning - Types of Games


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Artificial Intelligence and Machine Learning

CS3491 4th Semester CSE/ECE Dept | 2021 Regulation | 4th Semester CSE/ECE Dept 2021 Regulation