Abstract
While domain descriptions are often shared and manipulated through diagrams, most complex domains are still described using text-based languages. Code becomes an intermediary between the real-world and an abstract idea, and the programmer is merely a converter of diagrams into code. For automated planning this is no different. The state transition function is described in terms of a textual representation of actions and, although simple actions require little effort to define by the user, the learning process is often slow. New users have no metaphor to help them to visualize the domain description that they are working on and little information about why a planner fails due to formalization errors. In this paper, we propose a visual abstraction for both the planning domain actions and the planning process itself, to facilitate the design of classical planning domains. Using this abstraction, we expect to improve the learning curve for defining and subsequently diagnosing problems with new planning domains.
Original language | English |
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Title of host publication | Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016 |
Editors | Zdravko Markov, Ingrid Russell |
Publisher | AAAI Press |
Pages | 74-79 |
Number of pages | 6 |
ISBN (Electronic) | 9781577357568 |
Publication status | Published - 2016 |
Event | 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016 - Key Largo, United States Duration: 16 May 2016 → 18 May 2016 |
Publication series
Name | Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016 |
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Conference
Conference | 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016 |
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Country/Territory | United States |
City | Key Largo |
Period | 16/05/16 → 18/05/16 |
Bibliographical note
Publisher Copyright:© 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.