Abstract-Repairing an inconsistent knowledge base is a wellknown problem for which several solutions have been proposed and implemented in the past. In this paper, we start by looking at databases with active integrity constraints -consistency requirements that also indicate how the database should be updated when they are not met -as introduced by Caroprese et al. We show that the different kinds of repairs considered by those authors can be effectively computed by searching for leaves of specific kinds of trees. Although these computations are in general not very efficient (deciding the existence of a repair for a given database with active integrity constraints is N P -complete), on average the algorithms we present make significant reductions on the number of nodes in the search tree. Finally, these algorithms also give an operational characterization of different kinds of repairs that can be used when we extend the concept of active integrity constraints to the more general setting of knowledge bases.
In the design of resource bounded agents, high-level cognitive activities, such as reasoning, raise important problems related both to the adaptive ability and to the computational complexity of the underlying cognitive processes. To address these problems, we adopt an agent model where emotion and cognition are conceived as two integrated aspects of intelligent behavior and we present affective-emotional mechanisms that support the adaptation to changing environments and a controlled use of resources. These mechanisms produce an attention field that constrains the input to reasoning processes and also regulate the activation period of those processes. Experimental results are presented to illustrate this approach and to evaluate it by comparison with reference results concerning intention reconsideration policies.
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