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Ключевое слово reinforcement_learning [145 articles]

Recent papers classified by the tag reinforcement_learning.
  • Dopamine cells respond to predicted events during classical conditioning: evidence for eligibility traces in the reward-learning network.
    J Neurosci, Vol. 25, No. 26. (29 June 2005), pp. 6235-6242.
    by WX Pan, R Schmidt, JR Wickens, BI Hyland
    posted to dopamine_cells eligibility_trace reinforcement_learning by zhenbo_cheng on 2007-11-19 03:44:44 as ** along with 4 people and 1 group brian klouie dep stain Glimcher_Lab
  • Midbrain dopamine neurons encode decisions for future action
    Nature Neuroscience, Vol. 9, No. 8. (23 July 2006), pp. 1057-1063.
    by Genela Morris, Alon Nevet, David Arkadir, Eilon Vaadia, Hagai Bergman
    posted to dopomine_neuron reinforcement_learning by zhenbo_cheng on 2007-11-09 15:10:46 as * along with 5 people and 2 groups brian klouie Whyking nelmor sschafer Glimcher_Lab Computational-Neurobiology
  • Learning in spiking neural networks by reinforcement of stochastic synaptic transmission.
    Neuron, Vol. 40, No. 6. (18 December 2003), pp. 1063-1073.
    by HS Seung
    posted to reinforcement_learning stochastic_synaptic by zhenbo_cheng on 2007-11-19 01:34:43 as ** along with 3 people and 1 group brian garyfeng balicea ReadingLab
  • Machine Learning for Robotics: Learning Methods for Robot Motor Skills
    by Jan Peters
    posted to robots reinforcement_learning learning by vi_z on 2008-09-11 09:35:29 as *****
  • Identifying useful subgoals in reinforcement learning by local graph partitioning
    (2005), pp. 816-823.
    by özgür \csim\csek, Alicia P Wolfe, Andrew G Barto
    posted to subroals reinforcement_learning hierarchical by vi_z on 2008-09-09 21:15:59 as **
  • Reinforcement learning for a biped robot based on a CPG-actor-critic method
    Neural Netw., Vol. 20, No. 6. (2007), pp. 723-735.
    by Yutaka Nakamura, Takeshi Mori, Masa A Sato, Shin Ishii
    posted to robots reinforcement_learning actor-critic by vi_z on 2008-09-09 18:55:30 as ***
  • Reinforcement Learning-Based Feature Learning for Object Tracking
    icpr, Vol. 02 (2004), pp. 748-751.
    by Fang Liu, Jianbo Su
    posted to reinforcement_learning object_tracking learning feature_extraction by vi_z on 2008-09-09 20:15:06 as **
  • A reinforcement learning algorithm to improve scheduling search heuristics with the SVM
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on, Vol. 3 (2004), pp. 1811-1816 vol.3.
    by K Gersmann, B Hammer
    posted to svm reinforcement_learning learning by vi_z on 2008-09-09 18:54:40 as **
  • Recent advances in hierarchical reinforcement learning
    (2003)
    by A Barto, S Mahadevan
    posted to hierarchical reinforcement_learning survey by tdahl on 2008-03-08 21:35:11 as ** along with 1 person trvs2cool
  • Self-segmentation of Sequences: Automatic Formation of Hierarchies of Sequential Behaviors
    No. 609951-2781. (1999)
    by R Sun, C Sessions
    posted to hierarchical reinforcement_learning by tdahl on 2008-03-08 20:03:23 as **
  • Reinforcement Learning: A Survey
    Journal of Artificial Intelligence Research, Vol. 4 (1996), pp. 237-285.
    by Leslie P Kaelbling, Michael L Littman, Andrew P Moore
    posted to reinforcement_learning survey by tdahl on 2008-03-08 21:38:23 as ** along with 20 people and 5 groups KurtSteinkraus eldan unnonouno dep vaasu cyph3r davidmihalcik craigtalbert damcci hllee lop afoerster gagliol sugarexpletive mzygmunt dowlingj josepe docB bach Tominator Glimcher_Lab Netmob P2P SensorNetworks kickOffTUG-Robocup
  • Applications of the self-organising map to reinforcement learning
    Neural Networks, Vol. 15, No. 15. (2002), pp. 1107-1124.
    by Andrew J Smith
    posted to reinforcement_learning self_organizing_maps by tdahl on 2008-07-15 22:36:10 as **
  • Hidden state and reinforcement learning with instance-based state identification
    by A Mccallum
    posted to hidden_state instance_based reinforcement_learning by tdahl on 2008-07-15 14:51:42 as read
  • Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots
    (2000), pp. 671-678.
    by Daniel Nikovski, Illah Nourbakhsh
    posted to hidden_state model_based reinforcement_learning by tdahl on 2008-07-15 22:19:36 as **
  • Overcoming Incomplete Perception with Utile Distinction Memory
    (1993), pp. 190-196.
    by Andrew Mccallum
    posted to reinforcement_learning by tdahl on 2008-03-08 21:52:40 as **
  • Hierarchical reinforcement learning based on subgoal discovery and subpolicy specialization: First experiments with the HASSLE algorithm
    (2003)
    by B Bakker, J Schmidhuber
    posted to hierarchical reinforcement_learning by tdahl on 2008-03-08 21:40:04 as ** along with 1 person scis0000001
  • Policy gradient methods for reinforcement learning with function approximation
    Vol. 12 (2000), pp. 1057-1063.
    by Richard S Sutton, David Mcallester, Satinder Singh, Yishay Mansour
    posted to policy_gradient reinforcement_learning by tdahl on 2008-08-26 09:40:39 as *****
  • Model Based Learning for Mobile Robot Navigation from the Dynamical Systems Perspective
    IEEE Trans. Syst. Man and Cybern. B, Vol. 26, No. 3. (1996), pp. 421-436.
    by J Tani
    posted to hierarchical model_based neural_network reinforcement_learning by tdahl on 2008-07-15 21:55:23 as read
  • Discovering hierarchy in reinforcement learning with hexq
    (2002)
    by B Hengst
    posted to hierarchical reinforcement_learning by tdahl on 2008-07-15 14:46:09 as read along with 2 people Cavadini studentx
  • Learning hierarchical partially observable markov decision processes for robot navigation
    (2001)
    by G Theocharous, K Rohanimanesh, S Mahadevan
    posted to hidden_state hierarchical model_based reinforcement_learning by tdahl on 2008-07-15 22:17:04 as **
  • Real-time hierarchical POMDPs for autonomous robot navigation
    by A Foka, P Trahanias
    posted to hierarchical model_based reinforcement_learning by tdahl on 2008-07-15 22:23:55 as **
  • Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density
    (2001), pp. 361-368.
    by Amy Mcgovern, Andrew G Barto
    edited by Carla E Brodley, Andrea P Danyluk, Carla E Brodley, Andrea P Danyluk
    posted to hierarchical reinforcement_learning by tdahl on 2008-07-15 14:55:51 as read
  • Automatic basis function construction for approximate dynamic programming and reinforcement learning
    (2006), pp. 449-456.
    by Philipp W Keller, Shie Mannor, Doina Precup
    posted to reinforcement_learning function_approximation by tdahl on 2008-09-27 16:04:46 as ***
  • Overcoming incomplete perception with utile distinction memory
    (1993), pp. 190-196.
    by Andrew R Mccallum
    posted to hidden_state model_based reinforcement_learning by tdahl on 2008-08-11 21:13:26 as **
  • Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
    Artificial Intelligence, Vol. 112, No. 1-2. (1999), pp. 181-211.
    by Richard S Sutton, Doina Precup, Satinder P Singh
    posted to hierarchical reinforcement_learning by tdahl on 2008-03-08 21:43:21 as ** along with 1 person Scis0000002
  • Reinforcement learning with perceptual aliasing: The perceptual distinctions approach
    (1992), pp. 183-188.
    by Lonnie Chrisman
    posted to hidden_state model_based reinforcement_learning by tdahl on 2008-08-11 21:17:18 as **
  • Finding Structure in Reinforcement Learning
    Vol. 7 (1995), pp. 385-392.
    by Sebastian Thrun, Anton Schwartz
    edited by G Tesauro, D Touretzky, T Leen
    posted to hierarchical reinforcement_learning by tdahl on 2008-07-15 14:49:00 as *****
  • Hierarchical policy gradient algorithms
    Vol. 18 (2003), pp. 226-233.
    by Mohammad Ghavamzadeh, Sridhar Mahadevan
    posted to hierarchical policy_gradient reinforcement_learning by tdahl on 2008-08-26 09:43:02 as ****
  • Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
    (01 March 1998)
    by Richard S Sutton, Andrew G Barto
    posted to introduction reinforcement_learning survey by tdahl on 2008-05-01 10:21:09 as *** along with 18 people and 2 groups jerlich klouie oamg anoopsarkar creswick kmregan garyfeng mrkrause stain gonium nelmor awooga mzygmunt mak bsilverthorn robotact fbernardo lrozo Glimcher_Lab ReadingLab
  • How hierarchical control self-organizes in artificial adaptive systems
    Adaptive Behavior, Vol. 13, No. 13. (2005)
    by Rainer W Paine, Jun Tani, Rainer W Paine, Jun Tani
    posted to hierarchical model_based reinforcement_learning by tdahl on 2008-07-15 21:58:23 as *****
  • Reinforcement Learning with Hierarchies of Machines
    Vol. 10 (1997)
    by Ronald Parr, Stuart Russell
    edited by Michael I Jordan, Michael J Kearns, Sara A Solla
    posted to hierarchical reinforcement_learning by tdahl on 2008-03-08 21:45:45 as ** along with 1 person Blza
  • HQ-Learning
    Adaptive Behavior, Vol. 6, No. 2. (1997), pp. 219-246.
    by M Wiering, J Schmidhuber
    posted to hierarchical reinforcement_learning by tdahl on 2008-07-15 21:52:51 as read
  • Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition
    Journal of Artificial Intelligence Research, Vol. 13 (2000), pp. 227-303.
    by Thomas G Dietterich
    posted to hierarchical reinforcement_learning by tdahl on 2008-03-08 21:45:06 as ** along with 2 people rwm101 Maderlock
  • Reinforcement Learning for Problems with Hidden State
    by Samuel W Hasinoff
    posted to hidden_state problem reinforcement_learning by Sergi on 2005-10-12 09:14:22 as ** along with 5 people and 1 group noel garyfeng szityu shibu184 bsilverthorn ReadingLab
  • Learning the value of information in an uncertain world.
    Nat Neurosci (5 August 2007)
    by Timothy E J E Behrens, Mark W W Woolrich, Mark E E Walton, Matthew F S F Rushworth
    posted to decision_making fmri reinforcement_learning by sbarthelme on 2007-10-07 22:11:09 as read along with 6 people and 1 group sternshein nelmor shivakmr zhihui42 Gyoku quianominorleo VisionLab
  • Applications of the self-organising map to reinforcement learning
    Neural Netw., Vol. 15, No. 8-9. (2002), pp. 1107-1124.
    by Andrew J Smith
    posted to reinforcement_learning seminar som by satsumakenji on 2005-05-25 08:20:09 as **
  • On adaptation, maximization, and reinforcement learning among cognitive strategies.
    Psychological Review, Vol. 112, No. 4. (October 2005), pp. 912-931.
    by I Erev, G Barron
    posted to multiple_strategies reinforcement_learning by psimen on 2006-09-28 16:53:46 as read along with 1 person and 1 group garyfeng ReadingLab
  • Signal detection by human observers: a cutoff reinforcement learning model of categorization decisions under uncertainty.
    Psychological Review, Vol. 105, No. 2. (April 1998), pp. 280-298.
    by I Erev
    posted to criterion_adjustment reinforcement_learning by psimen on 2006-09-28 16:54:52 as read along with 1 person and 1 group garyfeng ReadingLab
  • Reinforcement learning in continuous time and space.
    Neural Computation, Vol. 12, No. 1. (January 2000), pp. 219-245.
    by K Doya
    posted to continuous_time reinforcement_learning by psimen on 2006-09-28 16:52:54 as read along with 2 people and 1 group garyfeng mura ReadingLab
  • Discrete coding of reward probability and uncertainty by dopamine neurons.
    Science, Vol. 299, No. 5614. (21 March 2003), pp. 1898-1902.
    by CD Fiorillo, PN Tobler, W Schultz
    posted to reinforcement_learning uncertainty vta by phystor on 2005-11-26 20:08:25 as ** along with 8 people and 4 groups klouie stefanherzog benoithv ifat krista awooga nishiokov farhat Glimcher_Lab CLIC logical_cognition ACS-Basel
  • Neural Encoding in Ventral Striatum during Olfactory Discrimination Learning
    Neuron, Vol. 38, No. 4. (22 May 2003), pp. 625-636.
    by Barry Setlow, Geoffrey Schoenbaum, Michela Gallagher
    posted to appetitive aversive reinforcement_learning reward striatal striatum ventral_striatum by oamg on 2007-04-02 14:38:17 as ***** along with 1 person and 1 group nelmor Glimcher_Lab
  • Biological arm motion through reinforcement learning.
    Biol Cybern, Vol. 91, No. 1. (July 2004), pp. 10-22.
    by J Izawa, T Kondo, K Ito
    posted to robot motor reinforcement_learning by oamg on 2005-03-14 18:18:23 as *** along with 1 person and 1 group balicea Glimcher_Lab
  • Adaptive Coding of Reward Value by Dopamine Neurons
    Science, Vol. 307, No. 5715. (11 March 2005), pp. 1642-1645.
    by Philippe N Tobler, Christopher D Fiorillo, Wolfram Schultz
    posted to decision-making dopamine learning monkey prediction_error reinforcement_learning by oamg on 2005-03-16 15:57:27 as ** along with 14 people and 4 groups jerlich klouie stefanherzog benoithv ifat reumir krista stain rchava awooga suizan mab2058 i-stevenson sschafer Glimcher_Lab CLIC logical_cognition ACS-Basel
  • Goal-directed instrumental action: contingency and incentive learning and their cortical substrates
    Neuropharmacology, Vol. 37, No. 4-5. (5 April 1998), pp. 407-419.
    by Bernard W Balleine, Anthony Dickinson
    posted to goal-directed incentive_learning instrumental_learning learning reinforcement_learning by oamg on 2007-07-23 19:30:24 as ** along with 2 people and 1 group nelmor josepe Glimcher_Lab
  • Reinforcement-related brain potentials from medial frontal cortex: origins and functional significance.
    Neurosci Biobehav Rev, Vol. 28, No. 4. (July 2004), pp. 441-448.
    by S Nieuwenhuis, CB Holroyd, N Mol, MG Coles
    posted to medial_frontal reinforcement_learning by oamg on 2007-02-21 01:26:24 as ***** along with 1 person and 1 group awooga Glimcher_Lab
  • Performance Feedback Drives Caudate Activation in a Phonological Learning Task
    J. Cogn. Neurosci., Vol. 18, No. 6. (1 June 2006), pp. 1029-1043.
    by Elizabeth Tricomi, Mauricio R Delgado, Bruce D Mccandliss, James L Mcclelland, Julie A Fiez
    posted to caudate instrumental_learning language perception reinforcement_learning striatum by oamg on 2007-05-16 18:25:05 as ** along with 1 group Glimcher_Lab
  • Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching
    : Advances in Artificial Life : 6th European Conference, ECAL 2001, Prague, Czech Republic, September 10-14, 2001, Proceedings (2001), 252.
    by Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Ruppin
    posted to loss_aversion matching reinforcement_learning uncertain_environments by oamg on 2007-04-19 17:49:12 as ** along with 1 group Glimcher_Lab
  • Dopamine D1 receptors involved in locomotor activity and accumbens neural responses to prediction of reward associated with place.
    Proc Natl Acad Sci U S A, Vol. 102, No. 6. (8 February 2005), pp. 2117-2122.
    by AH Tran, R Tamura, T Uwano, T Kobayashi, M Katsuki, T Ono
    posted to accumbens d1_receptor dopamine reinforcement_learning by oamg on 2005-03-16 15:35:22 as *** along with 1 group Glimcher_Lab
  • When artificial grammar acquisition in Parkinson's disease is impaired: The case of learning via trial-by-trial feedback
    Brain Research, Vol. 1067, No. 1. (5 January 2006), pp. 216-228.
    by Jared G Smith, John Mcdowall
    posted to artificial_grammar_acquisition parkinsons reinforcement_learning by oamg on 2007-02-27 04:08:29 as ***** along with 1 group Glimcher_Lab
  • Temporal sequence learning, prediction, and control: a review of different models and their relation to biological mechanisms.
    Neural Comput, Vol. 17, No. 2. (February 2005), pp. 245-319.
    by F Wörgötter, B Porr
    posted to conditioning reinforcement_learning by oamg on 2005-03-08 17:39:22 as **** along with 5 people and 1 group klouie stain josepe hukkinen mistersheik Glimcher_Lab
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