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    1. Hierarchical Reinforcement Learning

      http://duke.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LSwMxEA6iFy9Wq2C1yh7EgxCb3c1roRRKsRTBg8UinpY8rdCKaP3_5rXVogfvkzDZnckkk5nvA-DChUx3KEYcWhWyVUZCLiiCHnlFMWKQpr53-JHfPhX3Uz4eJZgc3wujF26eZXjC9z4tZCIewaRXYmcv1F3Pd9zVG3knHI7u1ruui0TpXRJBZ7goNsj-HOjjj1puxp_N7TfElHELzBptQkH1dSwoiamFjUrrBrLxf4rvg710yMyG0SoOwJZ5bYNWQ-CQJX8-BFeTF99_HOhQFll_PpiaAKSqQs4wS9irz_3efHAEZuObh9EEJvIEKApWrKDSWCIpPVhPSZgquKWiZBWySlBrGJbW6qqgrDCcWyS0h2Kz7jAkaVUKafLyGGREV1pSSTw_NbZGCpJLjEt3xzC5tNJ2QNutuX6LuBh1WmcHXDZfuFYJaNzzXSzq2ARNvgWztWAzxy-RbvOL6uRcH7XTOmeeMISe_KnAKdgtfJNCqOrrgu3V-6c5i2QP58FovgA5Brte

      by Tan, Ah-hwee; Subagdja, Budhitama; Pateria, Shubham and Quek, Chai

      Acm Computing Surveys, Volume 54, Issue 5, pp. 1 - 35

      Journal Article : Full Text Online

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    2. Deep learning, reinforcement learning, and world models

      http://duke.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1bS8MwFA7DJ1-cN3TeqOCjdU3TNhmMgc4V8c0b4lNI0sxNpI5d_r8nt8FgMFDoS9MT2vQk53xNv3MOQlfgMgEUJyweKrtbpWXMRJHEJvOKorlOqsLEDr-zx4_06ZmV_Qbqh1gYQ6v0tt_ZdGutfUvbv832ZDxuvyTgagsXKmpxDdhhQBNmZpf3d0trXDDHnAPh2EiH8DnL8ar1otaGUZmmNtWpqYa-3j2thZ-pd0NlE9VhAJaDfeM4KG43YoWcHbI8_nOsu2jHA9bo1sntoYau91EzFIOIvG04QIN7rSdRd9TzdSg-u-1R79o0TLXNzqrsRmS0elnUVWSTtka2JM_sEL2Vg9f-Q-xrNMQqo9k8lgBwAPXlWFFSpTolSlHJcK4VE0pgpggAJKmUpIJJUVSZrDAlmIisSoUQmByjKK86lSxkbspgZ0MtRY5llhH4lNFYDuWwhUjQCVc-c7kpoPHNA0XtiztNcqNJnhA4aAvFy14Tl7ljgzwN6uYrWuHgXDb0vAyzg8PiNH9cRK1_FjMO6AdsHsMUt9CRmzbLZwGgV3TA_p38-b6naNucOTriGdqaTxf63BW1uLCL4BdslQ9n

      by Sugiyama, Masashi; Matsuo, Yutaka; Precup, Doina; Morimoto, Jun; Sahani, Maneesh; LeCun, Yann; Silver, David and Uchibe, Eiji

      Neural Networks, Volume 152, pp. 267 - 275

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    3. Deep reinforcement learning in production systems: a systematic literature review

      http://duke.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV07TwMxDI54LDAgXhKFgjKwXrk87i6HqkpQWlVsICroFOVJkaqq6pX_T3JJXwNiYMlmD3Zix5b9fQDcupTpPsUpS6yqu1VGJkzkaeKRV1SRmVTnfnf4nT2P8Msr63fjNGEVxyp9DW0DUEQdq_3jFrJaTsT5DW6X6Chx1R1GLeTJlwjbBfvYs8u5K52OButgnLEIxJwmXma5xPObmq30tAVeuh2sScxA_WNwFL-O8CH4-gTsmOkpONwAFDwDH0_GzGB73JmbWqmqm38wUkN8tu_GHfg1hbMA8-pcAgOSc3UPBVyDOsPJCmwZht2WczDs9966gyRyJySKUrxIRFpKLERhtcpIKgzRVBVI6bwkppBaKK2xcsVMYWWmCEFG41LqMqcCSWUKQS4AzHSpZS4zT09NrZEiQ5JS4koMg6SVtgHo0lZcRURxT2wx4WgFPBpMzL2JeTRxA7RWYrMAqfGXQLnpCL6oexk2EI9w8odsc-k1Hl9nxXHOSj9WkLPLf6i-AgfY70L4Xi9pgr3F_NtcB06Jm_oSurP3OPwBS93cWA

      by Panzer, Marcel and Bender, Benedict

      International Journal Of Production Research, Volume 60, Issue 13, pp. 4316 - 4341

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    1. Reinforcement learning

      https://find.library.duke.edu/catalog/DUKE001047049

      edited by Richard S. Sutton.

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      Check Holdings for this item's availability Perkins & Bostock Library, Q325.6 .R45 1992 

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    2. Reinforcement Learning.

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    3. Reinforcement learning : an introduction

      https://find.library.duke.edu/catalog/DUKE008026227

      Richard S. Sutton and Andrew G. Barto.

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    1. Efficient approximate policy iteration methods for sequential decision making in reinforcement (...)

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      by Michail G. Lagoudakis.

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