Predicting The Performance of Minimax and Product in Game-Tree

03/27/2013
by   Ping-Chung Chi, et al.
0

The discovery that the minimax decision rule performs poorly in some games has sparked interest in possible alternatives to minimax. Until recently, the only games in which minimax was known to perform poorly were games which were mainly of theoretical interest. However, this paper reports results showing poor performance of minimax in a more common game called kalah. For the kalah games tested, a non-minimax decision rule called the product rule performs significantly better than minimax. This paper also discusses a possible way to predict whether or not minimax will perform well in a game when compared to product. A parameter called the rate of heuristic flaw (rhf) has been found to correlate positively with the. performance of product against minimax. Both analytical and experimental results are given that appear to support the predictive power of rhf.

READ FULL TEXT

page 1

page 2

page 4

page 6

research
03/27/2013

An Evaluation of Two Alternatives to Minimax

In the field of Artificial Intelligence, traditional approaches to choos...
research
06/02/2014

Monte Carlo Tree Search with Heuristic Evaluations using Implicit Minimax Backups

Monte Carlo Tree Search (MCTS) has improved the performance of game engi...
research
02/26/2019

Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?

World-class human players have been outperformed in a number of complex ...
research
04/05/2014

A New Paradigm for Minimax Search

This paper introduces a new paradigm for minimax game-tree search algo- ...
research
06/16/2017

Structured Best Arm Identification with Fixed Confidence

We study the problem of identifying the best action among a set of possi...
research
03/27/2013

A Cure for Pathological Behavior in Games that Use Minimax

The traditional approach to choosing moves in game-playing programs is t...
research
04/27/2019

Nonparametric feature extraction based on Minimax distance

We investigate the use of Minimax distances to extract in a nonparametri...

Please sign up or login with your details

Forgot password? Click here to reset