Agent-Based Optimization PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Agent-Based Optimization PDF full book. Access full book title Agent-Based Optimization by Ireneusz Czarnowski. Download full books in PDF and EPUB format.

Agent-Based Optimization

Agent-Based Optimization PDF Author: Ireneusz Czarnowski
Publisher: Springer
ISBN: 3642340970
Category : Technology & Engineering
Languages : en
Pages : 208

Book Description
This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.

Agent-Based Optimization

Agent-Based Optimization PDF Author: Ireneusz Czarnowski
Publisher: Springer
ISBN: 3642340970
Category : Technology & Engineering
Languages : en
Pages : 208

Book Description
This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.

Agent-Based Evolutionary Search

Agent-Based Evolutionary Search PDF Author: Ruhul A. Sarker
Publisher: Springer Science & Business Media
ISBN: 3642134254
Category : Technology & Engineering
Languages : en
Pages : 293

Book Description
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 and Individual-Based Modeling

Agent-Based and Individual-Based Modeling PDF Author: Steven F. Railsback
Publisher: Princeton University Press
ISBN: 0691190836
Category : Science
Languages : en
Pages : 358

Book Description
The essential textbook on agent-based modeling—now fully updated and expanded Agent-Based and Individual-Based Modeling has become the standard textbook on the subject for classroom use and self-instruction. Drawing on the latest version of NetLogo and fully updated with new examples, exercises, and an enhanced text for easier comprehension, this is the essential resource for anyone seeking to understand how the dynamics of biological, social, and other complex systems arise from the characteristics of the agents that make up these systems. Steven Railsback and Volker Grimm lead students stepwise through the processes of designing, programming, documenting, and doing scientific research with agent-based models, focusing on the adaptive behaviors that make these models necessary. They cover the fundamentals of modeling and model analysis, introduce key modeling concepts, and demonstrate how to implement them using NetLogo. They also address pattern-oriented modeling, an invaluable strategy for modeling real-world problems and developing theory. This accessible and authoritative book focuses on modeling as a tool for understanding real complex systems. It explains how to pose a specific question, use observations from actual systems to design models, write and test software, and more. A hands-on introduction that guides students from conceptual design to computer implementation to analysis Filled with new examples and exercises and compatible with the latest version of NetLogo Ideal for students and researchers across the natural and social sciences Written by two leading practitioners Supported by extensive instructional materials at www.railsback-grimm-abm-book.com

A Comparison of Agent-based Optimization Approaches Applied to the Weapons to Targets Assignment Planning Problem

A Comparison of Agent-based Optimization Approaches Applied to the Weapons to Targets Assignment Planning Problem PDF Author: Soneji Hitesh Deepak
Publisher:
ISBN:
Category : Combinatorial analysis
Languages : en
Pages : 58

Book Description
Real-world complex optimization problems are difficult to solve. Agent-based optimization approaches have proved useful in solving a wide variety of problems including optimization problems. Agent-based techniques can be used in military planning for solving allocation problems such as the weapons to targets assignment problem. Classical methods like linear programming (LP) have been used for solving weapons to targets assignment problems. LP approaches provide optimal solutions quickly, but in real-time planning when there are minor changes to input, LP exhibits widely varied solutions. This can be a problem in practice. This research study considers two agent-based optimization approaches, the Stable Marriage Algorithm (SMA) and the Ant-Colony Optimization (ACO) algorithm, for solving the weapons to targets assignment problem. In real-time defense planning and re-planning scenario, the effect of the input data changes on the solutions provided by SMA and ACO is observed. An interactive tool is developed in Visual Basic 6.0 for performing the assignment of weapons to targets using either of the agent-based optimization algorithms. An empirical analysis for determining the best parameter settings for finding good solutions for ACO algorithm is carried out. The performance of SMA and ACO is compared in terms of solution quality and persistence characteristics. Results indicate better performance of SMA than ACO in terms of persistence. In terms of solution quality, ACO provides solutions with lower assignment cost values than SMA.

Agent-Based Evolutionary Search

Agent-Based Evolutionary Search PDF Author: Ruhul A. Sarker
Publisher: Springer
ISBN: 9783642134241
Category : Mathematics
Languages : en
Pages : 291

Book Description
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.

Probability Collectives

Probability Collectives PDF Author: Anand Jayant Kulkarni
Publisher: Springer
ISBN: 3319160001
Category : Technology & Engineering
Languages : en
Pages : 162

Book Description
This book provides an emerging computational intelligence tool in the framework of collective intelligence for modeling and controlling distributed multi-agent systems referred to as Probability Collectives. In the modified Probability Collectives methodology a number of constraint handling techniques are incorporated, which also reduces the computational complexity and improved the convergence and efficiency. Numerous examples and real world problems are used for illustration, which may also allow the reader to gain further insight into the associated concepts.

Agent-Based Modeling and Simulation with Swarm

Agent-Based Modeling and Simulation with Swarm PDF Author: Hitoshi Iba
Publisher: CRC Press
ISBN: 1466562404
Category : Computers
Languages : en
Pages : 316

Book Description
Swarm-based multi-agent simulation leads to better modeling of tasks in biology, engineering, economics, art, and many other areas. It also facilitates an understanding of complicated phenomena that cannot be solved analytically. Agent-Based Modeling and Simulation with Swarm provides the methodology for a multi-agent-based modeling approach that i

Social, Cultural, and Behavioral Modeling

Social, Cultural, and Behavioral Modeling PDF Author: Robert Thomson
Publisher: Springer Nature
ISBN: 3030612554
Category : Computers
Languages : en
Pages : 365

Book Description
This book constitutes the proceedings of the 13th International Conference on Social, Cultural, and Behavioral Modeling, SBP-BRiMS 2020, which was planned to take place in Washington, DC, USA. Due to the COVID-19 pandemic the conference was held online during October 18–21, 2020. The 33 full papers presented in this volume were carefully reviewed and selected from 66 submissions. A wide number of disciplines are represented including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science. Numerous types of computational methods are used, such as machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics.

Spatial Microsimulation with R

Spatial Microsimulation with R PDF Author: Robin Lovelace
Publisher: CRC Press
ISBN: 131536316X
Category : Computers
Languages : en
Pages : 260

Book Description
Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data allocated to geographical zones. Spatial Microsimulation with R is the first practical book to illustrate this approach in a modern statistical programming language. Get Insight into Complex Behaviors The book progresses from the principles underlying population synthesis toward more complex issues such as household allocation and using the results of spatial microsimulation for agent-based modeling. This equips you with the skills needed to apply the techniques to real-world situations. The book demonstrates methods for population synthesis by combining individual and geographically aggregated datasets using the recent R packages ipfp and mipfp. This approach represents the "best of both worlds" in terms of spatial resolution and person-level detail, overcoming issues of data confidentiality and reproducibility. Implement the Methods on Your Own Data Full of reproducible examples using code and data, the book is suitable for students and applied researchers in health, economics, transport, geography, and other fields that require individual-level data allocated to small geographic zones. By explaining how to use tools for modeling phenomena that vary over space, the book enhances your knowledge of complex systems and empowers you to provide evidence-based policy guidance.

Multi-agent Optimization

Multi-agent Optimization PDF Author: Angelia Nedić
Publisher: Springer
ISBN: 3319971425
Category : Business & Economics
Languages : en
Pages : 310

Book Description
This book contains three well-written research tutorials that inform the graduate reader about the forefront of current research in multi-agent optimization. These tutorials cover topics that have not yet found their way in standard books and offer the reader the unique opportunity to be guided by major researchers in the respective fields. Multi-agent optimization, lying at the intersection of classical optimization, game theory, and variational inequality theory, is at the forefront of modern optimization and has recently undergone a dramatic development. It seems timely to provide an overview that describes in detail ongoing research and important trends. This book concentrates on Distributed Optimization over Networks; Differential Variational Inequalities; and Advanced Decomposition Algorithms for Multi-agent Systems. This book will appeal to both mathematicians and mathematically oriented engineers and will be the source of inspiration for PhD students and researchers.