Building Fitness Value Improvement using Evolutionary Process through Genetic Machine Learning Approach
نویسندگان
چکیده
Since decades developing programs for board games has been part of AI research and this field has attracted computer developers and researchers world-wide. Board games have a novel feature of simple, precise, easily formalized rules which makes them perfect launch vehicle to make computer game playing in a suitable development environment. The paper focuses on the two players, full knowledge, alternate move, deterministic, zero-sum game of Checkers. Genetic algorithmic approach is been applied in evolving computer player for the game of Checkers. The notion of this paper is to incorporate systematic game playing approach by analyzing game of checkers. Expert game players reveal three major playing
منابع مشابه
Power System Stability Improvement via TCSC Controller Employing a Multi-objective Strength Pareto Evolutionary Algorithm Approach
This paper focuses on multi-objective designing of multi-machine Thyristor Controlled Series Compensator (TCSC) using Strength Pareto Evolutionary Algorithm (SPEA). The TCSC parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a SPEA ...
متن کاملAnalysis and Improvement of Fitness Exploitation in XCS: Bounding Models, Tournament Selection, and Bilateral Accuracy
The evolutionary learning mechanism in XCS strongly depends on its accuracy-based fitness approach. The approach is meant to result in an evolutionary drive from classifiers of low accuracy to those of high accuracy. Since, given inaccuracy, lower specificity often corresponds to lower accuracy, fitness pressure most often also results in a pressure towards higher specificity. Moreover, fitness...
متن کاملFitness Value Optimization for Disc Set in Board Game through Evolutionary Learning
The Artificial Intelligence research field since ages has incorporated a series of novel and trend setting distinct approaches including neural networks, fuzzy logic and genetic algorithms to apply them to various problem-solving domains. Machine learning techniques such as evolutionary learning, neural networks and reinforcement learning alone are difficult to apply to board games because they...
متن کاملData-based melody generation through multi-objective evolutionary computation
Genetic-based composition algorithms are able to explore an immense space of possibilities, but the main difficulty has always been the implementation of the selection process. In this work, sets of melodies are utilized for training a machine learning approach to compute fitness, based on different metrics. The fitness of a candidate is provided by combining the metrics, but their values can r...
متن کاملExplain the theoretical and practical model of automatic facade design intelligence in the process of implementing the rules and regulations of facade design and drawing
Artificial intelligence has been trying for decades to create systems with human capabilities, including human-like learning; Therefore, the purpose of this study is to discover how to use this field in the process of learning facade design, specifically learning the rules and standards and national regulations related to the design of facades of residential buildings by machine with a machine ...
متن کامل