Modeling and Solving Methods for Complex Decision Tasks

Author: Yang Shanlin
Publisher:
Publish Date: 2007-01-01
Features: This book provides a systematic elaboration on the concepts, classification, and solution methods of complex decision-making tasks. Based on the analysis of Agent models, MAS system analysis, system design, and MAS models for complex decision-making tasks, it investigates modeling methods for Agent-based complex decision-making systems. By analyzing the structure of Bayesian networks and extended models, it explores the modeling processes and methods for Bayesian networks oriented towards complex decision-making tasks. The book systematically studies formal methods for decision-making Agents and task specification decomposition, task analysis and optimization decomposition methods, as well as genetic algorithm-based decomposition methods. It also examines collaborative solution mechanisms and approximate reasoning mechanisms for complex decision-making tasks. This book can serve as a textbook for senior undergraduate and graduate students in disciplines such as management science and engineering, decision science, systems science, control engineering, and computer application technology, and can also be referenced by relevant researchers.