Timezone: »
One of the main challenges in reinforcement learning is on solving tasks with sparse reward. We first show that the difficulty of discovering the rewarding state is bounded by the expected cover time of the underlying random walk induced by a policy. We propose a method to discover options automatically which reduce the cover time so as to speed up the exploration in sparse reward domains. We show empirically that the proposed algorithm successfully reduces the cover time, and improves the performance of the reinforcement learning agents.
Author Information
Yuu Jinnai (Brown University)
Jee Won Park (Brown University)
I am a senior in Applied Mathematics and research with Professor Konidaris at Brown University. My main interest is to use data to help people and make better decisions.
David Abel (Brown University)
George Konidaris (Brown)
Related Events (a corresponding poster, oral, or spotlight)
-
2019 Poster: Discovering Options for Exploration by Minimizing Cover Time »
Wed. Jun 12th 01:30 -- 04:00 AM Room Pacific Ballroom #117
More from the Same Authors
-
2023 : Guided Policy Search for Parameterized Skills using Adverbs »
Benjamin Spiegel · George Konidaris -
2023 Poster: Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning »
Sam Lobel · Akhil Bagaria · George Konidaris -
2023 Oral: Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning »
Sam Lobel · Akhil Bagaria · George Konidaris -
2023 Poster: Meta-learning Parameterized Skills »
Haotian Fu · Shangqun Yu · Saket Tiwari · Michael L. Littman · George Konidaris -
2023 Poster: RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agents »
Rafael A Rodriguez-Sanchez · Benjamin Spiegel · Jennifer Wang · Roma Patel · Stefanie Tellex · George Konidaris -
2021 : RL + Robotics Panel »
George Konidaris · Jan Peters · Martin Riedmiller · Angela Schoellig · Rose Yu · Rupam Mahmood -
2021 Poster: Skill Discovery for Exploration and Planning using Deep Skill Graphs »
Akhil Bagaria · Jason Senthil · George Konidaris -
2021 Oral: Skill Discovery for Exploration and Planning using Deep Skill Graphs »
Akhil Bagaria · Jason Senthil · George Konidaris -
2020 Poster: Learning Portable Representations for High-Level Planning »
Steven James · Benjamin Rosman · George Konidaris -
2019 Poster: Finding Options that Minimize Planning Time »
Yuu Jinnai · David Abel · David Hershkowitz · Michael L. Littman · George Konidaris -
2019 Oral: Finding Options that Minimize Planning Time »
Yuu Jinnai · David Abel · David Hershkowitz · Michael L. Littman · George Konidaris -
2018 Poster: State Abstractions for Lifelong Reinforcement Learning »
David Abel · Dilip S. Arumugam · Lucas Lehnert · Michael L. Littman -
2018 Oral: State Abstractions for Lifelong Reinforcement Learning »
David Abel · Dilip S. Arumugam · Lucas Lehnert · Michael L. Littman -
2018 Poster: Policy and Value Transfer in Lifelong Reinforcement Learning »
David Abel · Yuu Jinnai · Sophie Guo · George Konidaris · Michael L. Littman -
2018 Oral: Policy and Value Transfer in Lifelong Reinforcement Learning »
David Abel · Yuu Jinnai · Sophie Guo · George Konidaris · Michael L. Littman