Abstract
Contemporary automated planning research emphasizes the use of domain knowledge abstractions like heuristics to improve search efficiency. Transformative automated abstraction techniques which decompose or otherwise reformulate the problem have a limited presence, owing to poor performance in key metrics like plan length and time efficiency. In this paper, we argue for a reexamination of these transformative techniques in the context of narrative planning, where classical metrics are less appropriate. We propose a model for automating abstraction by decomposing a planning problem into subproblems which serve as abstract features of the problem. We demonstrate the application of this approach on a low-level problem and discuss key features of the resulting abstract problem. Plans in the abstract problem are shorter, representing summaries of low-level plans, but can be directly translated into low-level plans for the original problem.
Original language | English |
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Title of host publication | Proceedings - AAAI Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE |
Editors | Rogelio E. Cardona-Rivera, Seth Cooper |
Pages | 35-45 |
Number of pages | 11 |
Edition | 1 |
ISBN (Electronic) | 1577358953, 9781577358954 |
DOIs | |
State | Published - Nov 15 2024 |
Event | 20th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2024 - Lexington, United States Duration: Nov 18 2024 → Nov 22 2024 |
Publication series
Name | Proceedings - AAAI Artificial Intelligence and Interactive Digital Entertainment Conference, AIIDE |
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Number | 1 |
Volume | 20 |
ISSN (Print) | 2326-909X |
ISSN (Electronic) | 2334-0924 |
Conference
Conference | 20th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2024 |
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Country/Territory | United States |
City | Lexington |
Period | 11/18/24 → 11/22/24 |
Bibliographical note
Publisher Copyright:© 2024, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Human-Computer Interaction
- Software