Metaheuristics for Scheduling in Distributed Computing Environments Metaheuristics for Scheduling in Distributed Computing Environments

Metaheuristics for Scheduling in Distributed Computing Environments

    • US$209.99
    • US$209.99

출판사 설명

This volume is motivated in part by the observation that opposites permeate everything around us, in some form or another. Its study has attracted the attention of countless minds for at least 2500 years. However, due to the lack of an accepted mathematical formalism for opposition it has not been explicitly studied to any great length in fields outside of philosophy and logic. Despite the fact that we observe opposition everywhere in nature, our minds seem to divide the world into entities and opposite entities; indeed we use opposition everyday. We have become so accustomed to opposition that its existence is accepted, not usually questioned and its importance is constantly overlooked.

On the one hand, this volume is a fist attempt to bring together researchers who are inquiring into the complementary nature of systems and processes and, on the other hand, it provides some elementary components for a framework to establish a formalism for opposition-based computing. From a computational intelligence perspective, many successful opposition-based concepts have been in existence for a long time. It is not the authors intention to recast these existing methods, rather to elucidate that, while diverse, they all share the commonality of opposition - in one form or another, either implicitly or explicitly. Therefore they have attempted to provide rough guidelines to understand what makes concepts "oppositional".

장르
과학 및 자연
출시일
2008년
9월 8일
언어
EN
영어
길이
340
페이지
출판사
Springer Berlin Heidelberg
판매자
Springer Nature B.V.
크기
3.9
MB
Discovery Science Discovery Science
2007년
Adaptive Representations for Reinforcement Learning Adaptive Representations for Reinforcement Learning
2008년
Inductive Logic Programming Inductive Logic Programming
2014년
E-Expertise: Modern Collective Intelligence E-Expertise: Modern Collective Intelligence
2009년
Computational Intelligence in Expensive Optimization Problems Computational Intelligence in Expensive Optimization Problems
2010년
Learning and Intelligent Optimization Learning and Intelligent Optimization
2023년