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Research Article

Automating Pacman with Deep Q-Learning Using PYgame

  • Paper ID 507
  • Volume 3, Issue 3
  • Pages 437-439
  • Published Online: May-June 2022
  • 1 Views
Open Access Peer Reviewed

Authors

  • G.VIJAY KUMAR1
  • N. SAI KUMAR2
  • U.VARSHA3
  • SK.AFROZ4

1Assistant Professor, Computer Science and Engineering, CMR Technical Campus, Hyderabad, India. 234Student, Computer Science and Engineering, CMR Technical Campus, Hyderabad, India.

Article Information

DOI
No DOI
Published Online
May-June 2022
Pages
437-439
Article Type
Research Article
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No DOI available for cross-reference

References

[1] S. Adam, L. Bu¸soniu, R. Babuˇska, Systems Man and Cybernetics Part C: Applications and Reviews IEEE
Transactions on 2012, 42, 201–212.
[2] M. G. Bellemare, Y. Naddaf, J. Veness, M. Bowling, Journal of Artificial Intelligence Research 2012. [3] R. Bellman,
Indiana Univ. Math. J. 1957, 6, 679–684.
[4] R. E. Bellman, S. E. Dreyfus, Applied dynamic programming, Princeton university press, 2015.
[5] Berkeley Pacman project, http://ai.berkeley.edu/project_overview.html.
[6] T. J. Davidson, F. Kloosterman, M. A. Wilson, Neuron 2009, 63, 497–507.
[7] J. DeNero, D. Klein in Proceedings of the Symposium on Educational Advances in Artificial Intelligence, 2010.
[8] Google, Tensorflow, https : / / www . tensorflow . org / versions / r0 . 8 / get _ started / index.html, 2016.
[9] D. H. Hubel, T. N. Wiesel, The Journal of physiology 1968, 195, 215–243.
[10] A. Krizhevsky, I. Sutskever, G. E. Hinton in Advances in neural information processing systems, 2012, pp. 1097–1105
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