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 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.