Abstract
Hierarchical Task Networks (HTN) planning uses a decomposition process guided by domain knowledge to guide search towards a planning task. While many HTN planners allow calls to external processes (e.g.To a simulator interface) during the decomposition process, this is a computationally expensive process, so planner implementations often use such calls in an ad-hoc way using very specialized domain knowledge to limit the number of calls. Conversely, the classical planners that are capable of using external calls (often called semantic attachments) during planning are limited to generating a fixed number of ground operators at problem grounding time. We formalize Semantic Attachments for HTN planning using semi coroutines, allowing such procedurally defined predicates to link the planning process to custom unifications outside of the planner, such as numerical results from a robotics simulator. The resulting planner then uses such coroutines as part of its backtracking mechanism to search through parallel dimensions of the state-space (e.g.Through numeric variables).We show empirically that our planner outperforms the state-of-The-Art numeric planners in a number of domains using minimal extra domain knowledge.
Original language | English |
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Title of host publication | AAAI 2020 - 34th AAAI Conference on Artificial Intelligence |
Publisher | AAAI Press |
Pages | 9933-9940 |
Number of pages | 8 |
ISBN (Electronic) | 9781577358350 |
Publication status | Published - 2020 |
Externally published | Yes |
Event | 34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States Duration: 7 Feb 2020 → 12 Feb 2020 |
Conference
Conference | 34th AAAI Conference on Artificial Intelligence, AAAI 2020 |
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Country/Territory | United States |
City | New York |
Period | 7/02/20 → 12/02/20 |
Bibliographical note
Funding Information:Acknowledgements: We acknowledge the support given by CAPES/Pro-Alertas (88887.115590/2015-01) and CNPQ within process number 305969/2016-1 under the PQ fellowship. This paper was achieved in cooperation with HP Brasil Industria e Comercio de Equipamentos Eletronicos LTDA. using incentives of Brazilian Informatics Law (Law no 8.2.48 of 1991).
Publisher Copyright:
Copyright c 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.