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 20 of 2780 for “"Reinforcement"”.
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Direct Reinforcement, Vicarious Reinforcement and Reason in Behavior Modification
Made available in DSpace on 2014-12-08T21:25:18Z (GMT). No. of bitstreams: 1 6910836.pdf: 5557573 bytes, checksum: af7011393386d0e44c97120a17074a73 (MD5) Previous issue date: 1968
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Feature reinforcement learning agents
Reinforcement Learning (RL) is currently an active research area of Artificial Intelligence (AI) in which an agent interacts with an unknown environment in order to collect as much reward as possible. One of the most challenging problems in AI is the General Reinforcement Learning (GRL) problem …
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Feature reinforcement learning agents
Reinforcement Learning (RL) is currently an active research area of Artificial Intelligence (AI) in which an agent interacts with an unknown environment in order to collect as much reward as possible. One of the most challenging problems in AI is the General Reinforcement Learning (GRL) problem …
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Sample-efficient reinforcement learning
Reinforcement learning has been instrumental in the recent advances made by artificial intelligence agents in various domains. Most of these advances have been abetted by the availability of huge amounts of training data. But, in several practical applications such as those arising in wireless …
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Data Efficient Reinforcement Learning
Reinforcement learning (RL) has recently emerged as a generic yet powerful solution for learning complex decision-making policies, providing the key foundational underpinnings of recent successes in various domains, such as game playing and robotics. However, many state-of-the-art algorithms are …
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Effects of reinforcement history for following rules on sensitivity to contingencies of reinforcement
… manipulated subjects' experimental history of reinforcement for following rules in order to assess sensitivity to contingency changes. Ten undergraduate students were presented with four training tasks. Half the subjects were presented with instructions that corresponded with the reinforcement …
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Reinforced concrete beams: Investigation of stresses in web reinforcement and in logitudinal reinforcement
Made available in DSpace on 2014-09-18T16:15:30Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) reinforcedconcre00fish.pdf: 37394196 bytes, checksum: 954ccd7019738767c613cfc7d3361d94 (MD5) Previous issue date: 1914
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Circadian Influences in Cocaine Reinforcement
… associated with circadian influences in cocaine reinforcement. The central themes that run throughout are 24-hour cocaine self-administration and the impact of time-of-day and brain cocaine levels on cocaine taking.
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An Introduction to Reinforcement Learning
This thesis presents a new course textbook on reinforcement learning (RL) with a focus on algorithms and their properties. The textbook is suitable for a one-semester introductory undergraduate course on RL for students with prior experience in basic probability, linear algebra, and multivariable …
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Motivating Students Using Positive Reinforcement
… I researched the use of rewards and positive reinforcement with regards to behavior modification by creating a classroom behavior management plan called "Marbles for Manners". It was my intention that this reward system would positively reinforce students who used appropriate manners while …
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Differential Privacy in Reinforcement Learning
Reinforcement learning is a principled AI framework for autonomously experience-driven learning. The primary goal of reinforcement learning is to train autonomous agents to learn the optimal behaviors for their interactive environments. Deep reinforcement learning promotes a higher-level …
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CONDITIONED REINFORCEMENT FROM SHOCK TERMINATION.
… it is made contingent. This test for conditioned reinforcement is incomplete because multiple stimulus functions will be established during conditioning trials that can influence the rate of responding. The solution to this multiple stimulus control problem involved the effects of reinforcement …
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Secondary Reinforcement and Shock Termination
Made available in DSpace on 2014-12-03T23:51:03Z (GMT). No. of bitstreams: 1 5900492.pdf: 1349737 bytes, checksum: 5f680b6677797bdfee8ee1aba59c0703 (MD5) Previous issue date: 1958
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Deep reinforcement learning for quadrupeds
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms
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On Zero-Shot Reinforcement Learning
Modern reinforcement learning (RL) systems capture deep truths about general, human problem-solving. In domains where new data can be simulated cheaply, these systems uncover sequential decision-making policies that far exceed the ability of any human. Society faces many problems whose solutions …
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Reinforcement learning for telescope optimisation
Reinforcement learning is a relatively new and unexplored branch of machine learning with a wide variety of applications. This study investigates reinforcement learning and provides an overview of its application to a variety of different problems. We then explore the possible use of reinforcement …
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