Date Added: Apr 2009
Given a set of unquantified conditionals considered as default rules or a set of quantified conditionals such as probabilistic rules, an agent can build up its internal epistemic state from such a knowledge base by inductive reasoning techniques. Besides certain (logical) knowledge, epistemic states are supposed to allow the representation of preferences, beliefs, assumptions etc. of an intelligent agent. If the agent lives in a dynamic environment, it has to adapt its epistemic state constantly to changes in the surrounding world in order to be able to react adequately to new demands. In this paper, the authors present a high-level specification of the CONDOR system that provides powerful methods and tools for managing knowledge represented by conditionals and the corresponding epistemic states of an agent.