Agentbased Evolutionary Search

Agent-Based Evolutionary Search (Repost)  eBooks & eLearning

Posted by AvaxGenius at Sept. 20, 2023
Agent-Based Evolutionary Search (Repost)

Agent-Based Evolutionary Search by Ruhul Amin Sarker, Tapabrata Ray
English | PDF | 2010 | 293 Pages | ISBN : 3642134246 | 6.4 MB

Agent based evolutionary search is an emerging paradigm in computational int- ligence offering the potential to conceptualize and solve a variety of complex problems such as currency trading, production planning, disaster response m- agement, business process management etc. There has been a significant growth in the number of publications related to the development and applications of agent based systems in recent years which has prompted special issues of journals and dedicated sessions in premier conferences. The notion of an agent with its ability to sense, learn and act autonomously - lows the development of a plethora of efficient algorithms to deal with complex problems. This notion of an agent differs significantly from a restrictive definition of a solution in an evolutionary algorithm and opens up the possibility to model and capture emergent behavior of complex systems through a natural age- oriented decomposition of the problem space. While this flexibility of represen- tion offered by agent based systems is widely acknowledged, they need to be - signed for specific purposes capturing the right level of details and description. This edited volume is aimed to provide the readers with a brief background of agent based evolutionary search, recent developments and studies dealing with various levels of information abstraction and applications of agent based evo- tionary systems. There are 12 peer reviewed chapters in this book authored by d- tinguished researchers who have shared their experience and findings spanning across a wide range of applications.

Agent-Based Evolutionary Search (Adaptation, Learning, and Optimization) (Repost)  eBooks & eLearning

Posted by insetes at Jan. 7, 2018
Agent-Based Evolutionary Search (Adaptation, Learning, and Optimization) (Repost)

Agent-Based Evolutionary Search (Adaptation, Learning, and Optimization) By Ruhul Amin Sarker, Tapabrata Ray
2010 | 300 Pages | ISBN: 3642134246 | PDF | 6 MB
Why Are We Like This?: An Evolutionary Search for Answers to Life’s Big Questions

Why Are We Like This?: An Evolutionary Search for Answers to Life’s Big Questions by Zoe Kean
English | November 1st, 2024 | ISBN: 9781761179037 | 352 pages | True EPUB | 1.03 MB

What can snorkelling at Shark Bay teach us about humanity? Will the secrets of our sex lives be uncovered by stick insects? What do whale societies reveal about kindness? And why did we evolve to spend a third of our life asleep?

Numerical and Evolutionary Optimization 2018  eBooks & eLearning

Posted by roxul at Jan. 7, 2022
Numerical and Evolutionary Optimization 2018

, "Numerical and Evolutionary Optimization 2018"
English | ISBN: 3039218166 | 2019 | 230 pages | PDF | 27 MB

Knowledge Incorporation in Evolutionary Computation  eBooks & eLearning

Posted by roxul at Nov. 27, 2019
Knowledge Incorporation in Evolutionary Computation

Yaochu Jin, "Knowledge Incorporation in Evolutionary Computation "
English | ISBN: 3642061745 | 2004 | 564 pages | PDF | 50 MB

Evolutionary Computation in Combinatorial Optimization  eBooks & eLearning

Posted by AvaxGenius at May 14, 2021
Evolutionary Computation in Combinatorial Optimization

Evolutionary Computation in Combinatorial Optimization: 21st European Conference, EvoCOP 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings by Christine Zarges
English | PDF | 2021 | 249 Pages | ISBN : 3030729036 | 21.2 MB

This book constitutes the refereed proceedings of the 21st European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events: EvoMUSART, EvoApplications, and EuroGP.

Evolutionary Computation in Combinatorial Optimization  eBooks & eLearning

Posted by AvaxGenius at June 6, 2021
Evolutionary Computation in Combinatorial Optimization

Evolutionary Computation in Combinatorial Optimization: 21st European Conference, EvoCOP 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings by Christine Zarges
English | EPUB | 2021 | 249 Pages | ISBN : 3030729036 | 23.5 MB

This book constitutes the refereed proceedings of the 21st European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events: EvoMUSART, EvoApplications, and EuroGP.

Evolutionary Multi-Task Optimization  eBooks & eLearning

Posted by Free butterfly at Nov. 30, 2023
Evolutionary Multi-Task Optimization

Evolutionary Multi-Task Optimization: Foundations and Methodologies (Machine Learning: Foundations, Methodologies, and Applications) by Liang Feng, Abhishek Gupta, Kay Chen Tan
English | March 30, 2023 | ISBN: 9811956499 | 229 pages | MOBI | 16 Mb

Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms  eBooks & eLearning

Posted by AvaxGenius at Jan. 6, 2021
Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms

Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms by Oliver Schütze
English | PDF | 2021 | 242 Pages | ISBN : 3030637727 | 17.3 MB

This book presents an overview of archiving strategies developed over the last years by the authors that deal with suitable approximations of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All presented archivers are analyzed with respect to the approximation qualities of the limit archives that they generate and the upper bounds of the archive sizes.

Evolutionary and Adaptive Computing in Engineering Design  eBooks & eLearning

Posted by AvaxGenius at May 29, 2023
Evolutionary and Adaptive Computing in Engineering Design

Evolutionary and Adaptive Computing in Engineering Design by Ian C. Parmee
English | PDF | 2001 | 290 Pages | ISBN : 1852330295 | 30.6 MB

Prior to the early 1990s the term 'evolutionary computing' (EC) would have meant little to most practising engineers unless they had a particular interest in emerging computing technologies or were part of an organisation with significant in-house research activities. It was around this time that the first tentative utilisation of relatively simple evolutionary algorithms within engineering design began to emerge in the UK The potential was rapidly recognised especially within the aerospace sector with both Rolls Royce and British Aerospace taking a serious interest while in the USA General Electric had already developed a suite of optimisation software which included evolutionary and adaptiv,e search algorithms. Considering that the technologies were already twenty-plus years old at this point the long gestation period is perhaps indicative of the problems associated with their real-world implementation. Engineering application was evident as early as the mid-sixties when the founders of the various techniques achieved some success with computing resources that had difficulty coping with the population-based search characteristics of the evolutionary algorithms. Unlike more conventional, deterministic optimisation procedures, evolutionary algorithms search from a population of possible solutions which evolve over many generations. This largely stochastic process demands serious computing capability especially where objective functions involve complex iterative mathematical procedures.