In computing cooperative distributed problem solving is a
network of semi-autonomous processing nodes working together
to solve a problem, typically in a
multi-agent system. That is concerned with the investigation of problem subdivision, sub-problem distribution, results synthesis, optimisation of problem solver coherence and co-ordination. It is closely related to distributed
constraint programming
Constraint programming (CP) is a paradigm for solving combinatorial problems that draws on a wide range of techniques from artificial intelligence, computer science, and operations research. In constraint programming, users declaratively state t ...
and distributed constraint optimization; see the links below.
Aspects of CDPS
* Neither global control or global data storage – no individual CDPS problem solver (agent) has sufficient information to solve the entire problem.
* Control and data are distributed
* Communication is slower than computation, therefore:
** Loose coupling between problem solvers
** Efficient protocols (not too much communication overhead)
** problems should be modular, coarse grained
* Any unique node is a potential bottleneck
** Organised behaviour is hard to guarantee since no one node has the complete picture
See also
*
Multiscale decision making
*
Distributed constraint optimization
*
Distributed artificial intelligence
*
Multi-agent planning
Some relevant books
* A chapter in an edited book.
*
* See Chapters 1 and 2
downloadable free online
*
Applications of distributed computing
Problem solving
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