Data Portal @ linkeddatafragments.org

Matches in DBpedia 2014 for { <http://dbpedia.org/resource/Reinforcement_learning> ?p ?o. }

• Reinforcement_learning abstract "Reinforcement learning is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. The problem, due to its generality, is studied in many other disciplines, such as game theory, control theory, operations research, information theory, simulation-based optimization, statistics, and genetic algorithms. In the operations research and control literature, the field where reinforcement learning methods are studied is called approximate dynamic programming. The problem has been studied in the theory of optimal control, though most studies there are concerned with existence of optimal solutions and their characterization, and not with the learning or approximation aspects. In economics and game theory, reinforcement learning may be used to explain how equilibrium may arise under bounded rationality.In machine learning, the environment is typically formulated as a Markov decision process (MDP), and many reinforcement learning algorithms for this context are highly related to dynamic programming techniques. The main difference between the classical techniques and reinforcement learning algorithms is that the latter do not need knowledge about the MDP and they target large MDPs where exact methods become infeasible.Reinforcement learning differs from standard supervised learning in that correct input/output pairs are never presented, nor sub-optimal actions explicitly corrected. Further, there is a focus on on-line performance, which involves finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge). The exploration vs. exploitation trade-off in reinforcement learning has been most thoroughly studied through the multi-armed bandit problem and in finite MDPs.".
• Reinforcement_learning wikiPageExternalLink repository.php.
• Reinforcement_learning wikiPageExternalLink summary?doi=10.1.1.129.8871.
• Reinforcement_learning wikiPageExternalLink summary?doi=10.1.1.143.857.
• Reinforcement_learning wikiPageExternalLink ewrl.wordpress.com.
• Reinforcement_learning wikiPageExternalLink glue.rl-community.org.
• Reinforcement_learning wikiPageExternalLink glue.rl-community.org.
• Reinforcement_learning wikiPageExternalLink rl_algs.html.
• Reinforcement_learning wikiPageExternalLink download.htm.
• Reinforcement_learning wikiPageExternalLink jaksch10a.html.
• Reinforcement_learning wikiPageExternalLink mmlf.sourceforge.net.
• Reinforcement_learning wikiPageExternalLink mor.pubs.informs.org.
• Reinforcement_learning wikiPageExternalLink or.pubs.informs.org.
• Reinforcement_learning wikiPageExternalLink Successes_Of_RL.
• Reinforcement_learning wikiPageExternalLink teachingbox.php.
• Reinforcement_learning wikiPageExternalLink piqle.
• Reinforcement_learning wikiPageExternalLink rlai.
• Reinforcement_learning wikiPageExternalLink Successes-of-Reinforcement-Learning.
• Reinforcement_learning wikiPageExternalLink dpchapter.pdf.
• Reinforcement_learning wikiPageExternalLink behaviorism.
• Reinforcement_learning wikiPageExternalLink the-book.html.
• Reinforcement_learning wikiPageExternalLink PhDthesis.
• Reinforcement_learning wikiPageExternalLink TD_paper.
• Reinforcement_learning wikiPageExternalLink code.html.
• Reinforcement_learning wikiPageExternalLink www-all.cs.umass.edu.
• Reinforcement_learning wikiPageExternalLink rlr.
• Reinforcement_learning wikiPageExternalLink peters-ICHR2003.pdf.
• Reinforcement_learning wikiPageExternalLink orngReinforcement.htm.
• Reinforcement_learning wikiPageExternalLink ndpbook.html.
• Reinforcement_learning wikiPageExternalLink adp.htm.
• Reinforcement_learning wikiPageExternalLink hybrid-rl.html.
• Reinforcement_learning wikiPageExternalLink new_thesis.pdf.
• Reinforcement_learning wikiPageExternalLink kaelbling96a.html.
• Reinforcement_learning wikiPageExternalLink rlbook.
• Reinforcement_learning wikiPageExternalLink media.html.
• Reinforcement_learning wikiPageExternalLink automatica.
• Reinforcement_learning wikiPageExternalLink PolicyGradientToolbox.
• Reinforcement_learning wikiPageExternalLink Peters2010_REPS.pdf.
• Reinforcement_learning wikiPageExternalLink 546.pdf.
• Reinforcement_learning wikiPageExternalLink ril-toolbox.
• Reinforcement_learning wikiPageExternalLink www.jair.org.
• Reinforcement_learning wikiPageExternalLink www.jmlr.org.
• Reinforcement_learning wikiPageExternalLink ttt.html.
• Reinforcement_learning wikiPageExternalLink ~ieeetac.
• Reinforcement_learning wikiPageExternalLink www.pybrain.org.
• Reinforcement_learning wikiPageExternalLink Reinforcement_Learning.
• Reinforcement_learning wikiPageExternalLink Temporal_difference_learning.
• Reinforcement_learning wikiPageExternalLink 10994.
• Reinforcement_learning wikiPageExternalLink KI2011.pdf.
• Reinforcement_learning wikiPageExternalLink vid.php?a=Stanford&c=Machine+Learning&l=Applications+of+Reinforcement+Learning.
• Reinforcement_learning wikiPageExternalLink www.wintersim.org.
• Reinforcement_learning wikiPageExternalLink watch?v=RtxI449ZjSc&feature=relmfu.
• Reinforcement_learning wikiPageID "66294".
• Reinforcement_learning wikiPageRevisionID "600619909".
• Reinforcement_learning hasPhotoCollection Reinforcement_learning.
• Reinforcement_learning subject Category:Belief_revision.
• Reinforcement_learning subject Category:Machine_learning_algorithms.
• Reinforcement_learning subject Category:Markov_models.
• Reinforcement_learning type Assistant109815790.
• Reinforcement_learning type CausalAgent100007347.
• Reinforcement_learning type LivingThing100004258.
• Reinforcement_learning type MarkovModels.
• Reinforcement_learning type Model110324560.
• Reinforcement_learning type Object100002684.
• Reinforcement_learning type Organism100004475.
• Reinforcement_learning type Person100007846.
• Reinforcement_learning type PhysicalEntity100001930.
• Reinforcement_learning type Whole100003553.
• Reinforcement_learning type Worker109632518.
• Reinforcement_learning type YagoLegalActor.
• Reinforcement_learning type YagoLegalActorGeo.
• Reinforcement_learning comment "Reinforcement learning is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. The problem, due to its generality, is studied in many other disciplines, such as game theory, control theory, operations research, information theory, simulation-based optimization, statistics, and genetic algorithms.".
• Reinforcement_learning label "Apprendimento per rinforzo".
• Reinforcement_learning label "Apprentissage par renforcement".
• Reinforcement_learning label "Aprendizaje por refuerzo".
• Reinforcement_learning label "Bestärkendes Lernen".
• Reinforcement_learning label "Reinforcement learning".
• Reinforcement_learning label "Обучение с подкреплением".
• Reinforcement_learning label "強化学習".
• Reinforcement_learning label "强化学习".
• Reinforcement_learning sameAs Zpětnovazební_učení.
• Reinforcement_learning sameAs Bestärkendes_Lernen.
• Reinforcement_learning sameAs Ενισχυτική_μάθηση.
• Reinforcement_learning sameAs Aprendizaje_por_refuerzo.
• Reinforcement_learning sameAs Apprentissage_par_renforcement.
• Reinforcement_learning sameAs Apprendimento_per_rinforzo.
• Reinforcement_learning sameAs 強化学習.
• Reinforcement_learning sameAs 강화_학습.
• Reinforcement_learning sameAs m.0hjlw.
• Reinforcement_learning sameAs Q830687.
• Reinforcement_learning sameAs Q830687.
• Reinforcement_learning sameAs Reinforcement_learning.
• Reinforcement_learning wasDerivedFrom Reinforcement_learning?oldid=600619909.
• Reinforcement_learning isPrimaryTopicOf Reinforcement_learning.