Abstract
Intention (and its change, if any) is an indispensable step in the process from belief to action in various types of human behavior. Although the notion of intention has been originally investigated in philosophy and psychology at first, and then was modeled and formalized in Artificial Intelligence, traditional research has focused so much attention on the static properties of intention, but its dynamic properties have received much less attention. However, in a changing world, intention of an agent may be changed before it leads into a real action and the last change and/or intention just before the real action is the most important in almost all cases. In order to provide a computational foundation for various advanced application systems where the key requirement is to accurately grasp intentions of agents/users just before their actions, this position paper proposes a new research direction: Computing intentions dynamically in a changing world by anticipatory relevant reasoning.
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Cheng, J. (2014). Computing Intentions Dynamically in a Changing World by Anticipatory Relevant Reasoning. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds) Intelligent Information and Database Systems. ACIIDS 2014. Lecture Notes in Computer Science(), vol 8398. Springer, Cham. https://doi.org/10.1007/978-3-319-05458-2_38
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DOI: https://doi.org/10.1007/978-3-319-05458-2_38
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