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Representing Action: Indeterminacy and Ramifications (1997)
Enrico Giunchiglia, G. Neelakantan Kartha and
Vladimir Lifschitz
We define and study a high-level language for describing actions, more expressive than the action language A introduced by Gelfond and Lifschitz. The new language, AR, allows us to describe actions with indirect effects (ramifications), nondeterministic actions, and actions that may be impossible to execute. It has symbols for nonpropositional fluents and for the fluents that are exempt from the commonsense law of inertia. Temporal projection problems specified using the language AR can be represented as nested abnormality theories based on the situation calculus.
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Citation:
Artificial Intelligence
, Vol. 95 (1997), pp. 409-443.
Bibtex:
@ARTICLE{giu97a, title={Representing Action: Indeterminacy and Ramifications}, author={Enrico Giunchiglia and G. Neelakantan Kartha and Vladimir Lifschitz}, volume={95}, journal={Artificial Intelligence}, pages={409-443}, url="http://www.cs.utexas.edu/users/ai-lab?giu97a", year={1997} }
People
Vladimir Lifschitz
Faculty
vl [at] cs utexas edu
Areas of Interest
Action Languages
Common Sense Reasoning
Nonmonotonic Reasoning
Reasoning about Actions
Situation Calculus
Temporal Reasoning