Projektgruppe 642 (Sommersemester 2021)

Verteiltes Deep Reinforcement Learning System zum Trainieren von Game AI

Regelmäßiger betreuter Zeitraum

Freitags 9 - 12 Uhr

Discord

letzter Termin: 23.07.2021

PG Richtlinien und Modulhandbuch

Seminartermine

Thema Datum Uhrzeit Platform
Rainbow DQN 15.04.21 14:00 Uhr Zoom
Soft Actor-Critic 22.04.21 14:00 Uhr
Proximal Policy Optimization 29.04.21 14:00 Uhr
Never Give Up 06.05.21 14:00 Uhr

Folien

Nr. Thema Download
1 Kick-Off Meeting PG642-Kick-Off.pdf
2 Projektmanagement Workshop Teil I PG642-Projektmanagement-Workshop-1.pdf
2 Projektmanagement Workshop Teil II PG642-Projektmanagement-Workshop-2.pdf
3 Projektmanagement Workshop Teil III PG642-Projektmanagement-Workshop-3.pdf

Praktikum

Literatur

Bücher
  • R. S. Sutton and A. G. Barto : “Reinforcement Learning: An Introduction”, MIT Press, Cambridge, 2018 (ISBN: 9780262039246)
  • G. N. Yannakakis and J. Togelius : “Artificial Intelligence and Games”, Springer, 2018 (ISBN: 9783319635194)
  • M. Lapan: “Deep Reinforcement Learning Hands-On”, Packt Publishing, 2018 (ISBN: 9781788834247)
  • L. Graesser and W. L. Keng: “Foundations of Deep Reinforcement Learning”, Addison-Wesley Professional, 2019 (ISBN: 9780135172490)
  • M. Morales: “grokking Deep Reinforcement Learning”, Manning Publications Co., 2020 (ISBN: 9781617295454)
Paper/Tutorials
  • V. Mnih et al., “Human-level control through deep reinforcement learning”, Nat., vol. 518, no. 7540, pp. 529-533, 2015 K.Cobbe et al., “Leveraging procedural generation to benchmark reinforcement learning”, CoRR,vol. abs/1912.01588, 2019.
  • A. Juliani et al., “Obstacle tower: A generalization challenge in vision, control, and planning”, in Proceedings IJCAI 2019, Macao, China (S. Kraus, ed.), pp. 2684-2691, ijcai.org, 2019.
  • O. Vinyals et al., “Grandmaster level in starcraft II using multi-agent reinforcement learning”, Nat., vol. 575, no. 7782, pp. 350-354, 2019.
  • C. Berner et al., “Dota 2 with large scale deep reinforcement learning”, CoRR, vol. abs/ 1912.06680, 2019.
  • C. Hidber, “Reinforcement Learning: a gentle Introduction and industrial Application”, aufgerufen über https://youtu.b/3RjSanoNIlk am 14.12.2020, 2019.
  • M. Andrychowicz et al., “Learning dexterous in-hand manipulation”, Int. J. Robotics Res., vol. 39, no. 1, 2020.
  • M. G. Bellemare et al., “Autonomous navigation of stratospheric balloons using reinforcement learning”, Nat. vol. 588, pp.77-82, 2020.
 
Last modified: 2021-07-23 08:01 by Roman Kalkreuth
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