reinforcement learning

URI: https://gptkb.org/entity/reinforcement_learning

GPTKB entity

Predicate	Object
gptkbp:instanceOf	machine learning paradigm
gptkbp:application	autonomous vehicles robotics resource management game playing recommendation systems
gptkbp:challenge	credit assignment problem exploration-exploitation tradeoff sample efficiency stability and convergence
gptkbp:conference	gptkb:AAAI gptkb:ICML gptkb:NeurIPS gptkb:IJCAI
gptkbp:field	gptkb:artificial_intelligence
gptkbp:firstMajorBookPublished	1998
gptkbp:focusesOn	learning by trial and error
gptkbp:goal	maximize cumulative reward
gptkbp:hasSubfield	deep reinforcement learning hierarchical reinforcement learning inverse reinforcement learning model-based reinforcement learning model-free reinforcement learning multi-agent reinforcement learning
https://www.w3.org/2000/01/rdf-schema#label	reinforcement learning
gptkbp:involves	gptkb:public_policy environment states actions reward function value function agent
gptkbp:notableBook	gptkb:Reinforcement_Learning:_An_Introduction
gptkbp:notableContributor	gptkb:Andrew_Barto gptkb:Richard_S._Sutton
gptkbp:notableFor	gptkb:Monte_Carlo_methods gptkb:Actor-Critic gptkb:SARSA gptkb:Deep_Q-Network_(DQN)
gptkbp:relatedTo	gptkb:Q-learning Markov chain dynamic programming policy gradient methods temporal difference learning
gptkbp:usedBy	gptkb:DeepMind gptkb:AlphaGo gptkb:OpenAI_Five
gptkbp:uses	rewards and punishments
gptkbp:bfsParent	gptkb:artificial_intelligence gptkb:machine_learning gptkb:Theory_of_Machine_Learning
gptkbp:bfsLayer	4