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Revising its beliefs when receiving new information is an important ability of any intelligent system. However, in realistic settings the new input is not always certain. A compelling way of dealing with uncertain input in an agent-based setting is to treat it as unreliable input, which may strengthen or weaken the beliefs of the agent. Recent work focused on the postulates associated with this form of belief change and on finding semantical operators that satisfy these postulates. In this paper we propose a new syntactic approach for this form of belief change and show that it agrees with the semantical definition. This makes it feasible to develop complex agent systems capable of efficiently dealing with unreliable input in a semantically meaningful way. Additionally, we show that imposing restrictions on the input and the beliefs that are entailed allows us to devise a tractable approach suitable for resource-bounded agents or agents where reactiveness is of paramount importance.
|Title of host publication||Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Number of pages||8|
|Publication status||Published - 10 Nov 2014|
|Event||Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference - Limassol, Cyprus|
Duration: 10 Nov 2014 → 12 Nov 2014
|Conference||Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference|
|Period||10/11/2014 → 12/11/2014|
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