Recipe, Policy and Self-Organizing: A Hybrid Collaboration Approach for Agent-Based Cooperative Design

Cooperative design is distinguished from other cooperative behaviors by its inherent requirement for creativity. It is usually an ill-structured problem without complete and precise prescription. However, current agent-based cooperative design systems, which simply apply traditional multi-agent models to the domain of cooperative design, lack the adaptation to meet this essential requirement, so cannot be well applied. This paper proposes a hybrid multi-agent collaboration mode integrating determinate (recipe-guided) collaboration, policy-compliant collaboration and self-organizing mechanism for cooperative design. Determinate collaboration is suitable for those problems with determinate solutions in the design, while policy-compliant collaboration and self-organizing mechanism have advantages in dynamic regulations and loosely-coupled collaboration, which is necessary for creative work. They are complementary to each problem domain. Hence the hybrid mode is adaptive and flexible to broad organizing requirements of cooperative design process. The RPACPI agent model constructed for the hybrid collaboration mode is the core of the system, and thus formally specified in this paper. A case study is also given in this paper

[1]  Emil C. Lupu,et al.  The Ponder Policy Specification Language , 2001, POLICY.

[2]  Camelia Chira,et al.  A Multi-agent Architecture for Distributed Design , 2003, HoloMAS.

[3]  D. Capera,et al.  The AMAS theory for complex problem solving based on self-organizing cooperative agents , 2003, WET ICE 2003. Proceedings. Twelfth IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, 2003..

[4]  Timothy W. Finin,et al.  A policy language for a pervasive computing environment , 2003, Proceedings POLICY 2003. IEEE 4th International Workshop on Policies for Distributed Systems and Networks.

[5]  Liang Xiao,et al.  Collaborative design environment based on multi-agent , 2005, Proceedings of the Ninth International Conference on Computer Supported Cooperative Work in Design, 2005..

[6]  Hiroshi Yokoi,et al.  Self-organized norms of behavior under interactions of selfish agents , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[7]  Wassim Jabi,et al.  Reflections on computer-supported cooperative design systems , 2003 .

[8]  Jonathan Grudin,et al.  Computer-supported cooperative work: history and focus , 1994, Computer.

[9]  Jeffrey M. Bradshaw,et al.  KAoS policy and domain services: toward a description-logic approach to policy representation, deconfliction, and enforcement , 2003, Proceedings POLICY 2003. IEEE 4th International Workshop on Policies for Distributed Systems and Networks.

[10]  Chun Chen,et al.  CoDesign - a collaborative pattern design system based on agent , 2001, Proceedings of the Sixth International Conference on Computer Supported Cooperative Work in Design (IEEE Cat. No.01EX472).

[11]  Y. Shoham.  Introduction to Multi-Agent Systems , 2002 .

[12]  Jeffrey M. Bradshaw,et al.  Semantic Web Languages for Policy Representation and Reasoning: A Comparison of KAoS, Rei, and Ponder , 2003, SEMWEB.

[13]  Anne E. James,et al.  Multi-agent transactions for Web-based design activities , 2002, The 7th International Conference on Computer Supported Cooperative Work in Design.

[14]  Hong Liu,et al.  Sharing learning in a cooperative design system , 2001, Proceedings of the Sixth International Conference on Computer Supported Cooperative Work in Design (IEEE Cat. No.01EX472).

[15]  Weiming Shen,et al.  Semantic Integration in Distributed Multidisciplinary Design Optimization Environments , 2004, CSCWD.