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Research Article

Automating Pacman with Deep Q-Learning Using PYgame

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.

Published Online: May-June 2022

Pages: 437-439

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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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