Support for collaborative design: agents and emergence
Communications of the ACM
Communications of the ACM
An automated negotiation mechanism based on co-evolution and game theory
Proceedings of the 2002 ACM symposium on Applied computing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Electronic Commerce: Security Risk Management and Control
Electronic Commerce: Security Risk Management and Control
Issues in Multiagent Design Systems
IEEE Expert: Intelligent Systems and Their Applications
Architecture of an Agent-Based Negotiation Mechanism
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
Negotiating Agents in a Market-Oriented Grid
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
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In a complex engineering design, multiple engineering design teams are required to work cooperatively in order to design a single product. However multiple disciplinary teams in different departments and companies often use different systems with different modelling methods and techniques. While the parallelism of this approach can reduce the design life cycle, the complexity of the optimisation problem can lead to difficulties. Agent technology can alleviate some of the difficulties of concurrent design. In this paper, we present an architecture in which agent technology is used to model interactions between design systems, and thereby enable design agents from various design disciplines to explore the design problem and solution space. We also introduce a multiple-evolutionary approach with an automated negotiation mechanism to enable agents to exchange design solutions and to reach an agreed optimised solution for a global design problem.