Norms in artificial decision making

Artificial Intelligence and Law 7 (1):17-35 (1999)
Abstract
A method for forcing norms onto individual agents in a multi-agent system is presented. The agents under study are supersoft agents: autonomous artificial agents programmed to represent and evaluate vague and imprecise information. Agents are further assumed to act in accordance with advice obtained from a normative decision module, with which they can communicate. Norms act as global constraints on the evaluations performed in the decision module and hence no action that violates a norm will be suggested to any agent. Further constraints on action may then be added locally. The method strives to characterise real-time decision making in agents, in the presence of risk and uncertainty.
Keywords norm  constraint  real-time decision making  decisions with risk  decisions under uncertainty  vague information  policy  social space
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Martin Neumann (2012). The Cognitive Legacy of Norm Simulation. Artificial Intelligence and Law 20 (4):339-357.
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