Theory of Collective Intelligence

Summary In this chapter an analysis of the behavior of an arbitrary (perhaps massive) collective of computational processes in terms of an associated “world” utility function is presented We concentrate on the situation where each process in the collective can be viewed as though it were striving to maximize its own private utility function. For such situations the central design issue is how to initialize and update the collective's structure, in particular the private utility functions, so as to induce the overall collective to behave in a way that has large values of the world utility. Traditional “team game” approaches to this problem simply set each private utility function equal to the world utility function. The “collective intelligence” (COIN) framework is a semiformal set of heuristics that have recently been used to construct private utility functions that in many experiments have resulted in world utility values up to orders of magnitude superior to that ensuing from use of the team game utility. In this chapter we introduce a formal mathematics for analyzing and designing collectives. We also use this mathematics to suggest new private utilities that should outperform the COIN heuristics in certain kinds of domains. In accompanying work we use that mathematics to explain previous experimental results concerning the superiority of COIN heuristics. In that accompanying work we also use the mathematics to make numerical predictions, some of which we then test. In this way these two papers establish the study of collectives as a proper science, involving theory, explanation of old experiments, prediction concerning new experiments, and engineering insights.