Chess Player by Co-Evolutionary Algorithm

05/21/2016
by   Nuno Ramos, et al.
0

A co-evolutionary algorithm (CA) based chess player is presented. Implementation details of the algorithms, namely coding, population, variation operators are described. The alpha-beta or mini-max like behaviour of the player is achieved through two competitive or cooperative populations. Special attention is given to the fitness function evaluation (the heart of the solution). Test results on algorithms vs. algorithms or human player is provided.

READ FULL TEXT

page 2

page 3

page 4

page 5

page 6

page 7

page 8

research
07/06/2016

Rolling Horizon Coevolutionary Planning for Two-Player Video Games

This paper describes a new algorithm for decision making in two-player r...
research
01/21/2014

Reaserchnig the Development of the Electrical Power System Using Systemically Evolutionary Algorithm

The paper contains the concept and the results of research concerning th...
research
12/12/2009

Adapting Heuristic Mastermind Strategies to Evolutionary Algorithms

The art of solving the Mastermind puzzle was initiated by Donald Knuth a...
research
07/15/2014

Uncertainty And Evolutionary Optimization: A Novel Approach

Evolutionary algorithms (EA) have been widely accepted as efficient solv...
research
01/05/2020

Evolutionary Approach to Collectible Card Game Arena Deckbuilding using Active Genes

In this paper, we evolve a card-choice strategy for the arena mode of Le...
research
06/29/2023

Improving Time and Memory Efficiency of Genetic Algorithms by Storing Populations as Minimum Spanning Trees of Patches

In many applications of evolutionary algorithms the computational cost o...
research
01/09/2010

Incorporating characteristics of human creativity into an evolutionary art algorithm

A perceived limitation of evolutionary art and design algorithms is that...

Please sign up or login with your details

Forgot password? Click here to reset