Artificial intelligence: Learning to see and act

Nature

Volumn 518, Issue 7540, 2015, Pages 486-487

  Schölkopf, Bernhard ^a  

^a MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; INNOVATION; LEARNING;

ACCURACY; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; BEHAVIOR; BRAIN FUNCTION; DEEP Q NETWORK; EXPERIENTIAL LEARNING; HUMAN; LEARNING; MACHINE LEARNING; PRIORITY JOURNAL; RECREATION; REINFORCEMENT; REWARD; SHORT SURVEY; TASK PERFORMANCE;

ARTIFICIAL INTELLIGENCE; HUMANS; REINFORCEMENT (PSYCHOLOGY); VIDEO GAMES;

EID: 84924080712     PISSN: 00280836     EISSN: 14764687     Source Type: Journal    
DOI: 10.1038/518486a     Document Type: Short Survey

References (6)

1. Mnih, V. et al. Nature 518, 529-533 (2015).
2. Sutton R. S. & Barto A. G. Reinforcement Learning: An Introduction (MIT Press, 1998).
3. Watkins, C. J. C. H. Learning from Delayed Rewards. PhD thesis, Univ. Cambridge (1989).
4. Guo, X., Singh, S., Lee, H., Lewis, R. L. & Wang, X. Adv. Neural Inf. Process. Syst. 27 (2014).
5. Bareinboim, E. & Pearl, J. in Proc. 25th AAAI Conf. on Artificial Intelligence 100-108 (2011).
6. Schölkopf, B. et al. in Proc. 29th Int. Conf. on Machine Learning 1255-1262 (Omnipress, 2012).