Academic Journal
Planning with a Learned Policy Basis to Optimally Solve Complex Tasks
| العنوان: | Planning with a Learned Policy Basis to Optimally Solve Complex Tasks |
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| المؤلفون: | Kuric, David, Infante, Guillermo, Gómez, Vicenç, Jonsson, Anders, van Hoof, Herke |
| المصدر: | Proceedings of the International Conference on Automated Planning and Scheduling; Vol. 34 (2024): Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling; 333-341 ; 2334-0843 ; 2334-0835 |
| بيانات النشر: | Association for the Advancement of Artificial Intelligence |
| سنة النشر: | 2024 |
| المجموعة: | Association for the Advancement of Artificial Intelligence: AAAI Publications |
| الوصف: | Conventional reinforcement learning (RL) methods can successfully solve a wide range of sequential decision problems. However, learning policies that can generalize predictably across multiple tasks in a setting with non-Markovian reward specifications is a challenging problem. We propose to use successor features to learn a set of local policies that each solves a well-defined subproblem. In a task described by a finite state automaton (FSA) that involves the same set of subproblems, the combination of these local policies can then be used to generate an optimal solution without additional learning. In contrast to other methods that combine local policies via planning, our method asymptotically attains global optimality, even in stochastic environments. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | https://ojs.aaai.org/index.php/ICAPS/article/view/31492/33652; https://ojs.aaai.org/index.php/ICAPS/article/view/31492 |
| DOI: | 10.1609/icaps.v34i1.31492 |
| الاتاحة: | https://ojs.aaai.org/index.php/ICAPS/article/view/31492 https://doi.org/10.1609/icaps.v34i1.31492 |
| Rights: | Copyright (c) 2024 Association for the Advancement of Artificial Intelligence |
| رقم الانضمام: | edsbas.F92030C9 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1609/icaps.v34i1.31492 |
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