Abstract
One of the crucial capabilities for robust agency is self-assessment, namely, the capability of the agent to compute its own boundaries. A method of assessing these boundaries is using so-called expectations: constructs defining the boundaries of an agent’s courses of action as a function of the plan, the goals achieved by that plan, the initial state, the action model and the last action executed. In this paper we redefine four forms of expectations from the goal reasoning literature but, unlike those works, the agent reasons with durative actions. We present properties and a comparative study highlighting the trade offs between the expectations.
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Acknowledgments
This research was supported by ONR under grants N00014-18-1-2009 and N68335-18-C-4027 and NSF grant 1909879. The opinions in this paper are from the authors and not necessarily from the funding agencies.
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Reifsnyder, N., Munoz-Avila, H. (2022). Monitoring Goal Driven Autonomy Agent’s Expectations Generated from Durative Effects. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-82193-7_32
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DOI: https://doi.org/10.1007/978-3-030-82193-7_32
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