Why Social Sciences Do Need Nature Inspired Computing
For nearly four billions years, life has invaded Earth. Throughout
eras geological upheavals have deeply transformed the environment. Here,
deserts left place to a tropical environment; there ices were replaced
by conifers forests… Despite these transformations, life is so
vigorous that one can find it on the top of the highest mountains, in
the depths of oceans, as well as in clouds, or deep underground.
Darwinian natural adaptation has been transferred into Evolutionary Algorithms; Artificial Neural Networks are a metaphor of nervous systems; ants foraging behaviors gave rise to Ant Colony Optimization; birds flocks or fish schools inspired Particle Swarm Optimization; Artificial immune systems mimic the biological one; Insect or animal autonomy and abilities inspired Distributed Artificial Intelligence, Multi-Agent Systems and Artificial Societies…
In the fields of social sciences, economics and management, two types of contributions must be emphasized:
After a six chapters introduction to nature inspired computing for modeling and optimization, the first volume of the handbook is oriented toward social sciences (sociology and economics) modeling and experiments; the second volume mainly handles modeling, exploration and optimization for management.
The Social Modeling section includes seven chapters providing a global view of these researches. Chapters by Robert Axelrod and Harko Verhagen demonstrate the huge potential contribution of artificial societies to social sciences. Corruption, trust and academic science are then studied in the light of MAS, showing the cross-fertilization of social sciences and multi-agent systems.
The Economics section includes thirteen chapters providing with a global coverage of the use of nature inspired computing for economics. After an introduction to Agent-based Computational Economics (ACE), original researches using multi-agent systems, evolutionary algorithms or neural networks to deal with fundamental economic forces are presented. Clusters, innovation and technology are then particularly emphasized to enlighten the complex cross dynamics of space and technology.
Nature Inspired Computing and Management
The six sections, thirty two chapters second volume provides with a comprehensive coverage of the contributions of nature inspired computing to management. It shows its ability to solve problems beyond the capabilities of more traditional methods.
The first section, Design and Manufacturing, presents pioneering researches particularly using evolutionary algorithms. Applied to design, project management as well as to manufacturing, these researches clearly demonstrate the capacity of nature inspired algorithms to stimulate design creativity and to manage complex associated issues.
The second section, Operations and Supply Chain Management, contains twelve chapters. After an introduction to evolutionary optimization and ant colony optimization for operations management, main nature inspired tools are used to solve very diverse operations and supply chain management problems (scheduling, organization of production, distribution…). The section includes the presentation of a powerful Java framework designed to use evolutionary computation to solve operations and supply chain problems.
The section three, Information Systems, presents the novel agent oriented paradigm of information systems and provides with innovative researches, demonstrating the power and suppleness of nature inspired computing when applied to information management, e-learning and peer to peer systems.
The section four, Commerce and Negotiation, includes a synthesis of agents for multi-issue negotiation and presents original researches on automatic negotiations and auctions using agent-based modeling and evolutionary computation. These researches outstandingly lead the way toward future virtual organizations.
The section five, Marketing, uses evolutionary computation and agent-based modeling to analyze price wars and word-of-mouth and to contribute to the understanding of complex socio-economic systems to provide with a decision support tool for commercial organizations.
The section six¸ Finance, uses genetic programming, evolutionary computation, neural networks and agent-based modeling to deal with complex financial problems. They are applied to housing prices, financial decision aid, insurance-linked derivatives and stock-market simulations.
The fifty eight chapters of this two volumes handbook provide with a unique cross section of researches using nature inspired computing for economics and management. Social scientists, economists and people dealing with management science will find both an introduction and a valuable presentation of state of the art researches in these fields, giving them a unique reference tool for their researches. Students in computer sciences, social sciences and management will find all the necessary material to master the field and to help them in their training. Managers, engineers and practitioners will find a great deal of efficient and powerful tools to help them solve daily difficult problems and to anticipate the use of tools which will undoubtedly be part of to-morrow key success factors.
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