Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 5 of 5 for “"Temporal abstractions"”.
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The Limits of Temporal Abstractions for Reinforcement Learning with Sparse Rewards
Skills are temporal abstractions that are intended to improve reinforcement learning (RL) performance through hierarchical RL. Despite our intuition about the properties of an environment that make skills useful, there has been little theoretical work aimed to characterize these properties …
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Learning structured representations for perception and control
… learning algorithms, which produce and utilize temporally extended abstractions over actions. I also present a hybrid model-free and model-based deep reinforcement learning model, which can also be potentially used to automatically extract subgoals for bootstrapping temporal abstractions. I will …
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There Is Always an Option
… (HRL) addresses this problem by introducing temporal abstractions, often instantiated as options: temporally extended sequences of actions directed toward sub-goals. While prior work has largely focused on designing algorithms that explicitly learn such options, this work asks a different …
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Virtual articulation and kinematic abstraction in robotics
… kinostatic simulation, and novel kinematic abstractions, where complex subsystems are simplified with virtual replacements in both space and time. Decomposition algorithms, including a novel method of hierarchical subdivision, enable scaling to large closed-chain mechanisms with 100s of …
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A method to detect and represent temporal patterns from time series data and its application for analysis of physiological data streams
… making critical decisions about patient care. Temporal abstraction and data mining are two research fields that have tried to synthesize time oriented data to detect hidden relationships that may exist in the data. Various researchers have looked at techniques for generating abstractions from …