An approach to the pre-runtime design of normative systems for a class of problem-solving norm-regulated multi-agent systems is suggested. The basic idea is to employ evolutionary mechanisms to evolve efficient normative systems for so-called norm-regulated Dalmases, as part of the design process. The Dalmas architecture uses an algebraic approach to normative systems, in which normative consequences are based on an extended set of one-agent types of normative positions, which is given a semantics in terms of prohibition of certain types of state transitions. To illustrate the approach, a genetic algorithm is used to evolve norms for an example system. Furthermore, some approaches to reducing the algorithm’s search space, including to employ a notion of ‘operational equivalence’ of norms, are discussed. It is demonstrated that an evolutionary algorithm may be a useful tool when designing norms for problem-solving multi-agent systems.
CITATION STYLE
Hjelmblom, M. (2015). Offline norm evolution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9494, pp. 316–333). Springer Verlag. https://doi.org/10.1007/978-3-319-27947-3_17
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