Baral, C. and Gabaldon, A. and Provetti, Alessandro (1998) Formalizing narratives using nested circumscription. Artificial Intelligence 104 (1/2), pp. 107-164. ISSN 0004-3702.
Abstract
Representing and reasoning about narratives together with the ability to do hypothetical reasoning is important for agents in a dynamic world. These agents need to record their observations and action executions as a narrative and at the same time, to achieve their goals against a changing environment, they need to make plans (or re-plan) from the current situation. The early action formalisms did one or the other. For example, while the original situation calculus was meant for hypothetical reasoning and planning, the event calculus was more appropriate for narratives. Recently, there have been some attempts at developing formalisms that do both. Independently, there has also been a lot of recent research in reasoning about actions using circumscription. Of particular interest to us is the research on using high-level languages and their logical representation using nested abnormality theories (NATs)—a form of circumscription with blocks that make knowledge representation modular. Starting from theories in the high-level language , which is extended to allow concurrent actions, we define a translation to NATs that preserves both narrative and hypothetical reasoning. We initially use the high level language , and then extend it to allow concurrent actions. In the process, we study several knowledge representation issues such as filtering, and restricted monotonicity with respect to NATs. Finally, we compare our formalization with other approaches, and discuss how our use of NATs makes it easier to incorporate other features of action theories, such as constraints, to our formalization.
Metadata
| Item Type: | Article |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Depositing User: | Sarah Hall |
| Date Deposited: | 10 Aug 2021 08:31 |
| Last Modified: | 09 Aug 2023 12:51 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/45398 |
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