Multi-agent and Complex Systems [electronic resource] / edited by Quan Bai, Fenghui Ren, Katsuhide Fujita, Minjie Zhang, Takayuki Ito.
Contributor(s): Bai, Quan [editor.] | Ren, Fenghui [editor.] | Fujita, Katsuhide [editor.] | Zhang, Minjie [editor.] | Ito, Takayuki [editor.] | SpringerLink (Online service).
Material type: BookSeries: Studies in Computational Intelligence: 670Publisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: VIII, 210 p. 73 illus., 43 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789811025648.Subject(s): Dynamics | Nonlinear theories | Artificial intelligence | Computational intelligence | Computer networks | Economic sociology | Applied Dynamical Systems | Artificial Intelligence | Computational Intelligence | Computer Communication Networks | Economic SociologyAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 515.39 Online resources: Click here to access online1.Adaptive Forwarder Selection for Distributed Wireless Sensor Networks -- 2.Trust Transference on Social Exchanges among Triads of Agents Based on Dependence Relations and Reputation -- 3.A Multiagent-Based Domain Transportation Approach for Optimal Resource Allocation in Emergency Management -- 4.A proto-type of a portable ad hoc simple water gauge and real world evaluation -- 5.Exploiting Vagueness for Multi-Agent Consensus 6.Selecting Robust Strategies Based on Abstracted Game Models -- 7.Simulating and Modeling Dual Market Segmentation Using PSA Framework -- 8.CORPNET: Towards a Decision Support System for Organizational Network Analysis using Multiplex Interpersonal Relations -- 9.Membership Function Based Matching Approach of Buyers and Sellers Through a Broker in Open E-Marketplace -- 10.The Effect of Assertiveness and Empathy on Heider's Balance Theory for Friendship Network Models information on submission -- 11.Associative Memory-based Approach to Multi-task Reinforcement Learning under Stochastic Environments -- 12.Preliminary Estimating Method of Opponent's Preferences using Simple Weighted Functions for Multi-lateral Closed Multi-issue Negotiations -- 13.Multi-Objective Nurse Rerostering Problem -- 14.Preference Aware Influence Maximization -- 15.Norm Emergence through Collective Learning and Information Diffusion in Complex Relationship Networks -- 16.Agent-Based Computation of Decomposition Games with Application in Software Requirements Decomposition.
This book provides a description of advanced multi-agent and artificial intelligence technologies for the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field. A complex system features a large number of interacting components, whose aggregate activities are nonlinear and self-organized. A multi-agent system is a group or society of agents which interact with others cooperatively and/or competitively in order to reach their individual or common goals. Multi-agent systems are suitable for modeling and simulation of complex systems, which is difficult to accomplish using traditional computational approaches.
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