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.