About this item
- Title
- VASE: Variational Assorted Surprise Exploration for Reinforcement Learning
- Content partner
- University of Otago
- Collection
- Otago University Research Archive
- Description
Exploration in environments with continuous control and sparse rewards remains a key challenge in reinforcement learning (RL). One of the approaches to encourage more systematic and efficient exploration relies on surprise as an intrinsic reward for the agent. We introduce a new definition of surprise and its RL implementation named variational assorted surprise exploration (VASE). VASE uses a Bayesian neural network as a model of the environment dynamics and is trained using variational infe...
- Format
- Research paper
- Research format
- Scholarly text / Journal article
- Thesis level
- Article
- Date created
- 2023-03
- Creator
- Xu, Haitao / Szymanski, Lech / McCane, Brendan
- URL
- https://hdl.handle.net/10523/23643
- Related subjects
- Bayes methods / Bayesian neural network (BNN) / Computational modeling / exploration / Neural networks / Predictive models / Probability distribution / Reinforcement learning / reinforcement learning (RL) / surprise / Training / variational inference
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Report this itemDigitalNZ brings together more than 30 million items from institutions so that they are easy to find and use. This information is the best information we could find on this item. This item was added on 21 August 2024, and updated 09 October 2024.
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