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 4 of 4 for “"Arcade Learning Environment"”.
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Addressing stale gradients in asynchronous federated deep reinforcement learning
Advancements in reinforcement learning (RL) via deep neural networks have enabled their application to a variety of real-world problems. However, these applications often suffer from long training times. While attempts to distribute training have been successful in controlled scenarios, they face …
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Universal artificial intelligence: evaluation and benchmarks
… be used to analyze one promising platform - the Arcade Learning Environment (ALE) that integrates Atari 2600 games to test domain independent artificial agents. We will suggest practical ways to incorporate these features into the ALE platform to manage limitations of computing resources used to …
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Generic Reinforcement Learning Beyond Small MDPs
Feature reinforcement learning (FRL) is a framework within which an agent can automatically reduce a complex environment to a Markov Decision Process (MDP) by finding a map which aggregates similar histories into the states of an MDP. The primary motivation behind this thesis is to build FRL agents …
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Generic Reinforcement Learning Beyond Small MDPs
Feature reinforcement learning (FRL) is a framework within which an agent can automatically reduce a complex environment to a Markov Decision Process (MDP) by finding a map which aggregates similar histories into the states of an MDP. The primary motivation behind this thesis is to build FRL agents …