Abstract
Knowledge and causality play an essential role in the attempt to achieve commonsense reasoning in cognitive robotics. As agents usually operate in dynamic and uncertain environments, they need to acquire information through sensing inertial aspects, such as the state of a door, and continuously changing aspects, such as the location of a moving object. In this paper, we extend an Event Calculus-based knowledge framework with a method for sensing world features of different types in a uniform and transparent to the agent manner. The approach results in the modeling of agents that remember and forget, a cognitive skill particularly suitable for the implementation of real-world applications.
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Patkos, T., Plexousakis, D. (2009). Sensing Inertial and Continuously-Changing World Features. In: Iliadis, Maglogiann, Tsoumakasis, Vlahavas, Bramer (eds) Artificial Intelligence Applications and Innovations III. AIAI 2009. IFIP International Federation for Information Processing, vol 296. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-0221-4_45
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DOI: https://doi.org/10.1007/978-1-4419-0221-4_45
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