Modular redundancy, in which a function is performed by multiple, redundant agents machines or humans requires an 'adjudication' stage to produce a single 'opinion' out of the multiple ones produced. Commonly used adjudication functions are, e.g. majority voting and averaging of the multiple results, but many alternatives are possible and in actual use. The adjudication problem has also emerged as a key part in distributed cognition systems where the decision making process is inferred from a set of multiple agents. The choice of an adjudication function is of paramount importance for the overall dependability of a redundant system. This problem has been addressed separately by scholars in different disciplines, e.g. in the normative study of group decision making and in computer design. Each discipline has typically addressed a specific set of scenarios, with its own assumptions, which we believe would be of interest in other disciplines as well. All can benefit from taking into account results developed in other disciplines, and seeing their separate sets of assumptions and results in a common framework. This chapter explains the adjudication problem, investigates the different criteria that help the designer in choosing an appropriate adjudication function and proves some interesting properties that characterize an optimal adjudication function, given a specific utility function and failure hypothesis for the system in which it is to be used.

Inspec keywords: cognitive systems; redundancy; decision making; failure analysis; cognition

Other keywords: redundant system dependability; modular redundancy; decision making process; redundant agent machine; failure hypothesis; multiple agent; distributive cognition; majority voting; utility function; adjudication problem; adjudication function; distributed cognition system

Subjects: Applications of systems theory