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タグ: reinforcement_learning [134 articles]

Recent papers classified by the tag reinforcement_learning.
  • 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
  • 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
  • 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
  • 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 reinforcement_learning hierarchical by tdahl on 2008-07-15 14:55:51 as read
  • Hidden state and reinforcement learning with instance-based state identification
    by A Mccallum
    posted to reinforcement_learning instance_based hidden_state by tdahl on 2008-07-15 14:51:42 as read
  • 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 reinforcement_learning hierarchical by tdahl on 2008-07-15 14:49:00 as *****
  • Discovering hierarchy in reinforcement learning with hexq
    (2002)
    by B Hengst
    posted to reinforcement_learning hierarchical by tdahl on 2008-07-15 14:46:09 as read along with 2 people studentx Cavadini
  • 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 self_organizing_maps reinforcement_learning by tdahl on 2008-07-15 22:36:10 as **
  • Real-time hierarchical POMDPs for autonomous robot navigation
    by A Foka, P Trahanias
    posted to reinforcement_learning model_based hierarchical by tdahl on 2008-07-15 22:23:55 as **
  • Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots
    (2000), pp. 671-678.
    by Daniel Nikovski, Illah Nourbakhsh
    posted to reinforcement_learning model_based hidden_state by tdahl on 2008-07-15 22:19:36 as **
  • Learning hierarchical partially observable markov decision processes for robot navigation
    (2001)
    by G Theocharous, K Rohanimanesh, S Mahadevan
    posted to reinforcement_learning model_based hierarchical hidden_state by tdahl on 2008-07-15 22:17:04 as **
  • Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)
    (01 March 1998)
    by Richard S Sutton, Andrew G Barto
    posted to survey reinforcement_learning introduction by tdahl on 2008-05-01 10:21:09 as *** along with 17 people and 2 groups fbernardo jerlich klouie oamg anoopsarkar creswick kmregan garyfeng mrkrause stain gonium nelmor awooga mzygmunt mak bsilverthorn robotact 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 reinforcement_learning model_based hierarchical by tdahl on 2008-07-15 21:58:23 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 reinforcement_learning neural_network model_based hierarchical by tdahl on 2008-07-15 21:55:23 as read
  • 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 **
  • HQ-Learning
    Adaptive Behavior, Vol. 6, No. 2. (1997), pp. 219-246.
    by M Wiering, J Schmidhuber
    posted to reinforcement_learning hierarchical by tdahl on 2008-07-15 21:52:51 as read
  • 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 **
  • 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
  • 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
  • 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
  • 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
  • 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 Tominator KurtSteinkraus eldan unnonouno dep vaasu cyph3r davidmihalcik craigtalbert damcci hllee lop afoerster gagliol sugarexpletive mzygmunt dowlingj josepe docB bach Glimcher_Lab Netmob P2P SensorNetworks kickOffTUG-Robocup
  • 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
  • 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 quianominorleo sternshein nelmor shivakmr zhihui42 Gyoku 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 **
  • 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
  • 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
  • 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 7 people and 4 groups nishiokov klouie stefanherzog benoithv ifat krista awooga Glimcher_Lab CLIC logical_cognition ACS-Basel
  • Opponent interactions between serotonin and dopamine
    Neural Networks, Vol. 15, No. 4-6. ( 2002), pp. 603-616.
    by Nathaniel D Daw, Sham Kakade, Peter Dayan
    posted to decision-making dopamine reinforcement_learning serotonin by oamg on 2007-04-19 17:07:46 as *** along with 1 person and 1 group awooga Glimcher_Lab
  • A framework for mesencephalic dopamine systems based on predictive Hebbian learning
    J. Neurosci., Vol. 16, No. 5. (1 March 1996), pp. 1936-1947.
    by Pr Montague, P Dayan, Tj Sejnowski
    posted to actor_critic dopamine hebbian_learning reinforcement_learning by oamg on 2007-04-30 21:53:31 as ** along with 1 person and 1 group stain Glimcher_Lab
  • Self-organizing neural systems based on predictive learning.
    Philos Transact A Math Phys Eng Sci, Vol. 361, No. 1807. (15 June 2003), pp. 1149-1175.
    by RP Rao, TJ Sejnowski
    posted to bees reinforcement_learning temporal_difference by oamg on 2007-05-03 14:22:26 as ** along with 1 person and 1 group amorgan77 Glimcher_Lab
  • Cortico-striatal contributions to feedback-based learning: converging data from neuroimaging and neuropsychology.
    Brain, Vol. 127, No. Pt 4. (April 2004), pp. 851-859.
    by D Shohamy, CE Myers, S Grossman, J Sage, MA Gluck, RA Poldrack
    posted to observational_learning reinforcement_learning by oamg on 2007-06-01 17:17:35 as ** along with 1 group Glimcher_Lab
  • Subcortical control of dopamine neurons: the good, the bad and the unexpected.
    Brain Res Bull, Vol. 71, No. 1-3. (11 December 2006), pp. 1-3.
    by RD Stewart, EJ Dommett
    posted to dopamine reinforcement_learning reward_prediction_error by oamg on 2007-02-26 20:15:08 as *** along with 4 people and 1 group brian sschafer awooga rcoreilly Glimcher_Lab
  • Reward or reinforcement: what's the difference?
    Neurosci Biobehav Rev, Vol. 13, No. 2-3. (l 1989), pp. 181-186.
    by NM White
    posted to learning psychology reinforcement reinforcement_learning reward striatum terminology by oamg on 2007-02-26 20:10:24 as *** along with 4 people and 1 group brian dep nelmor mistersheik Glimcher_Lab
  • Reward prediction in primate basal ganglia and frontal cortex
    Neuropharmacology, Vol. 37, No. 4-5. (5 April 1998), pp. 421-429.
    by Wolfram Schultz, Leon Tremblay, Jeffrey R Hollerman
    posted to basal_ganglia dopamine frontal_cortex neurophysiology primate reinforcement_learning reward single-unit by oamg on 2007-07-23 19:32:57 as ** along with 1 person and 1 group josepe Glimcher_Lab
  • Computational roles for dopamine in behavioural control
    Nature, Vol. 431, No. 7010. (14 October 2004), pp. 760-767.
    by Read P Montague, Steven E Hyman, Jonathan D Cohen
    posted to behavior dopamine reinforcement_learning by oamg on 2007-05-02 16:35:05 as ** along with 7 people and 1 group nishiokov shoshin brian bayesian makimaki nelmor josepe 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
  • Reward, motivation, and reinforcement learning.
    Neuron, Vol. 36, No. 2. (10 October 2002), pp. 285-298.
    by P Dayan, BW Balleine
    posted to motivation reinforcement_learning rewar by oamg on 2007-05-02 16:33:38 as ** along with 3 people and 2 groups brian stefanherzog awooga Glimcher_Lab 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
  • 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 i-stevenson jerlich klouie stefanherzog benoithv ifat reumir krista stain rchava sschafer awooga suizan mab2058 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. (y 1998), pp. 407-419.
    by BW Balleine, A Dickinson
    posted to incentive_learning instrumental_conditioning pavlovian_conditioning reinforcement_learning by oamg on 2007-06-01 14:46:39 as ** along with 1 group Glimcher_Lab
  • Policy adjustment in a dynamic economic game.
    PLoS ONE, Vol. 1 (2006)
    by J Li, SM McClure, B King-Casas, P Read Montague
    posted to game policy reinforcement_learning by oamg on 2007-04-19 18:33:17 as ** along with 1 group Glimcher_Lab
  • Learning to Predict by the Methods of Temporal Differences
    Machine Learning, Vol. 3 (1988), pp. 9-44.
    by Richard S Sutton
    posted to reinforcement_learning temporal_difference by oamg on 2007-04-17 18:59:06 as ** along with 6 people and 5 groups brian garyfeng dep pverstra gonium afoerster Glimcher_Lab ReadingLab macc SensorNetworks Computational Learning Theory
  • Reinforcement learning signals predict future decisions.
    J Neurosci, Vol. 27, No. 2. (10 January 2007), pp. 371-378.
    by MX Cohen, C Ranganath
    posted to erp reinforcement_learning by oamg on 2007-02-21 01:42:11 as ** along with 3 people and 2 groups garyfeng nelmor Vezhnick Glimcher_Lab ReadingLab
  • 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
  • Parsing reward.
    Trends Neurosci, Vol. 26, No. 9. (September 2003), pp. 507-513.
    by KC Berridge, TE Robinson
    posted to dopamine macaque neurphysiology reinforcement_learning reward by oamg on 2005-04-07 15:20:13 as **** along with 3 people and 1 group klouie yaroslavvb gsk3 Glimcher_Lab
  • Motivation concepts in behavioral neuroscience.
    Physiol Behav, Vol. 81, No. 2. (April 2004), pp. 179-209.
    by KC Berridge
    posted to dopamine reinforcement_learning by oamg on 2005-04-07 15:17:57 as *** along with 3 people and 5 groups stefanherzog benoithv suizan Glimcher_Lab CLIC logical_cognition ACS-Basel 801
  • Ventral-striatal/nucleus-accumbens sensitivity to prediction errors during classification learning.
    Hum Brain Mapp, Vol. 27, No. 4. (April 2006), pp. 306-313.
    by PF Rodriguez, AR Aron, RA Poldrack
    posted to instrumental_conditioning nucleus_accumbens reinforcement_learning reward_prediction_error ventral_striatum by oamg on 2007-06-01 16:46:08 as ** along with 1 group Glimcher_Lab
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