Handbook of Research on Nature Inspired Computing for Economics and Management A book edited by Jean-Philippe Rennard, Grenoble Graduate
School of Business, Grenoble, France. Home - Table of Contents - Preface - Brochure |
Table of Contents Download the full TOC with abstracts HERE Volume 1: Nature Inspired Computing and Social
Sciences Foreword: A
Cure for Dismal Science Section 1.1-Nature Inspired Computing 1. A
Brief Introduction to Artificiality in Social Sciences 2. Multi-Cellular
Techniques: from Social Insects to Collective Robotics 3. Stochastic
Optimization Algorithms 4. Evolutionary
algorithms: A Quick Presentation 5. Genetic
Programming 6. An
Introduction to Evolutionary Multi-Objective Optimization
Section 1.2- Social Modeling 7. Advancing
the Art of Simulation in the Social Sciences 8. Multiagent
Systems Research and Social Science Theory 9. A
Dynamic Agent-Based Model of Corruption 10. Human
Nature in the Adaptation of Trust 11. Cognitively-Based
Simulation of Academic Science 12. Application
of Nature-Inspired Knowledge Mining Algorithms for Emergent Behavior
Discovery in Economic Models 13. The
Grid for Nature Inspired Computing and Complex Simulations: Possible
Applications Allowed by the Technological State of the Art Section 1.3- Economics 14. Agent-Based
Computational Economics-An Introduction 15. Data
gathering to build and validate small-scale social models for simulation.
Two ways: strict control and stake-holders involvement 16. Modeling
Qualitative Development -Agent Based Approaches in Economics 17. Agent-based
Modeling with Boundedly Rational agents 18. Heterogeneous
Learning Using Genetic Algorithms: Communication versus Experiments 19. Modeling
the Firm as an Artificial Neural Network 20. Evolutionary
Modeling as an Alternative Explanation of Industrial Structure Emergence 21. Population
Symbiotic Evolution in a model of Industrial Districts 22. Competitive
advantage of Geographical Clusters: A Complexity Science Approach and
an Agent-based Simulation Study 23. A
Simulation of Strategic Bargainings within Biotechnology Clusters 24. Knowledge
Accumulation in Hayekian Market Process Theory under Limited Imitability
Assumptions 25. On
Technological Specialization in Industrial Clusters: An Agent-based
Analysis 26. Simulating
Product Invention using InventSim Volume 2: Nature Inspired Computing and Management Section 2.1- Design and Manufacturing 27. Human-centric
Evolutionary Systems in Design and Decision-Making 28. Double
Duty: Genetic Algorithms for Organizational Design and Genetic Algorithms
Inspired by Organizational Theory 29. Autonomous
Systems with Emergent Behavior 30. An
Evolutionary Algorithm for Decisional Assistance to Project Management 31. Pareto-optimality
in Design and Manufacturing and how Genetic Algorithms handle it
32. Evolutionary
Optimization in Production Research 33. Ant
Colony Optimization and Multiple Knapsack Problem 34. A
new way to Reorganize a Productive Department in Cells through the Help
of the Ant Behavior 35.
Agent-Oriented Modeling and Simulation of Distributed Manufacturing 36.
Application of RAP/AOR to the Modeling and Simulation of a Ceramic
Factory 37.
Building Distribution Networks Using Cooperating Agents 38.
Games, Supply chains and Automatic Strategy Discovery using Evolutionary
Computation 39.
Applications of Neural Networks in Supply Chain Management 40.
JGA: An Object-Oriented Framework for Rapid Development of Genetic
Algorithms 41.
Applications of JGA to Operations Management and Vehicle Routing 42.
Solving Facility Location Problems using a Tool for Rapid Development
of Multi-Objective Evolutionary Algorithms (MOEAs) 43.
Worker Performance Modeling in Manufacturing. Simulation: Proposition
of an Agent-Based Approach Section 2.3- Information Systems 44.
Towards An Agent-Oriented Paradigm of Information Systems 45.
Caste-centric Development of Agent Oriented Information 46.
Evolving Learning Ecologies 47.
Efficient Searching in Peer-to-Peer Networks using Agent Enabled
Ant Algorithms Section 2.4- Commerce and Negotiation 48.
An Annealing Protocol for Negotiating Complex Contracts 49.
Agents for Multi-Issue Negotiation 50.
An introduction to Evolutionary Computation in Auctions: the Ausubel
Format 51.
Supporting Virtual Organizations through Electronic Institutions
and Normative Multi-Agent Systems Section 2.5-Marketing 52.
Co-evolving Better Strategies in Oligopolistic Price Wars 53.
Social Anti-Percolation, Resistance and Negative Word-of-Mouth 54.
Complexity Based Modeling Approaches for Commercial Applications Section 2.6-Finance 55.
Spatiotemporal Forecasting of Housing Prices by Use of Genetic Programming 56.
Multiattribute Methodologies in Financial Decision Aid 57.
Multiobjective Optimization Evolutionary Algorithms for Mathematical
Models of underlying catastrophic loss index of Insurance-Linked Derivatives 58.
Modeling an Artificial Stock market: When Information Influence Market
Dynamics |