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In a Trusted Desktop Grid agents cooperate to improve the speedup of their calculations. Since it is an open  system, the behaviour of agents can not be foreseen. In previous work we have introduced a trust metric to cope  with this information uncertainty. Agents rate each other and exclude undesired behaving agents. Previous  implementations of agents used hardcoded logic for those ratings. In this paper, we propose an approach to  convert implicit rules to explicit norms. This allows learning agents to understand the expected behavior and  helps us to provide an improved reaction to attacks by changing norms.

Influence of Norms on Decision Making in Trusted Desktop Grid Systems - Making Norms Explicit