Abstract
An autonomous agent is one that is not only directed by its environment, but is also driven by internal motivation to achieve certain goals. The popular Belief-Desire-Intention (BDI) design paradigm allows such agents to adapt to environmental changes by calculating a new execution path to their current goal, or when necessary turning to another goal. In this paper we present an approach to modelling autonomous agents using an extension to Object-Z. This extension supports both data and action refinement, and includes the use of LTL formulas to describe an agent’s desire as a sequence of prioritised goals. It turns out, however, that the introduction of desire-driven behaviour is not monotonic with respect to refinement. We therefore introduce an additional refinement proof obligation to enable the use of simulation rules when checking refinement.
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Li, Q., Smith, G. (2013). A Refinement Framework for Autonomous Agents. In: Iyoda, J., de Moura, L. (eds) Formal Methods: Foundations and Applications. SBMF 2013. Lecture Notes in Computer Science, vol 8195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41071-0_12
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DOI: https://doi.org/10.1007/978-3-642-41071-0_12
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