Fuzzy sets and applications
International Journal of Human-Computer Studies - Special issue: real-world applications of uncertain reasoning
Communications of the ACM
Knowledge-Based Intelligent Techniques in Industry
Knowledge-Based Intelligent Techniques in Industry
Communication infrastructure in distributed scheduling
Computers and Industrial Engineering - 26th International conference on computers and industrial engineering
Multi-agent-based integrated framework for intra-class testing of object-oriented software
Applied Soft Computing
An evolutionary compensatory negotiation model for distributed dynamic scheduling
Applied Soft Computing
Agent-based bilateral multi-issue negotiation scheme for e-market transactions
Applied Soft Computing
Negotiation Process for Multi-Agent DSS for Manufacturing System
Proceedings of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges
Supporting a multicriterion decision making and multi-agent negotiation in manufacturing systems
Intelligent Decision Technologies
A knowledge-based architecture for distributed fault analysis in power networks
Engineering Applications of Artificial Intelligence
Applications of agent-based models for optimization problems: A literature review
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
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The advent of multiagent systems, a branch of distributed artificial intelligence, introduced a new approach to problem solving through agents interacting in the problem solving process. In this paper, a collaborative framework of a distributed agent-based intelligence system is addressed to control and resolve dynamic scheduling problem of distributed projects for practical purposes. If any delay event occurs, the self-interested activity agent, the major agent for the problem solving of dynamic scheduling in the framework, can automatically cooperate with other agents in real time to solve the problem through a two-stage decision-making process: the fuzzy decision-making process and the compensatory negotiation process. The first stage determines which behavior strategy will be taken by agents while delay event occurs, and prepares to next negotiation process; then the compensatory negotiations among agents are opened related with determination of compensations for respective decisions and strategies, to solve dynamic scheduling problem in the second stage. A prototype system is also developed and simulated with a case to validate the problem solving of distributed dynamic scheduling in the framework.