Abstract
In the Distributed Artificial Intelligence community, the term “Distributed Problem Solving (DPS)” is widely used. However, different people refer to different types of DPS frameworks. In this paper, we define a comprehensive framework for Distributed Problem Solving. Firstly, we clarify four different types of basic DPS frameworks: DPS1 for task unique-allocation problems, DPS2 for task multi-allocation problems, DPS3 for task decomposition problems, and DPS4 for task division problems. Then, we define the comprehensive framework which can be different combinations of DPS1, DPS2, DPS3, and DPS4.
In this framework, Solution Integration (SI) is a necessary component. Three different types of Solution Integration are identified: Solution Synthesis, Solution Composition, and Solution Construction which correspond to DPS2, DPS3 and DPS4, respectively.
The definition of the four basic DPS frameworks and the establishment of the comprehensive framework for DPS will hopefully lead to a better understanding and implementation of DPS systems.
This work was partially supported by the large grant from the Australian Research Council (A49530850). H. Yang is also funded by the Overseas Postgraduate Research Scholarship and The University of New England Research Scholarship, Australia.
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© 1996 Springer-Verlag Berlin Heidelberg
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Yang, H., Zhang, C. (1996). Definition and application of a comprehensive framework for distributed problem solving. In: Zhang, C., Lukose, D. (eds) Distributed Artificial Intelligence Architecture and Modelling. DAI 1995. Lecture Notes in Computer Science, vol 1087. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61314-5_17
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DOI: https://doi.org/10.1007/3-540-61314-5_17
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