/RL-paper-collection

Collection of notes and RL paper that I read

Contain notes on paper on Reinforcement Learning that I read. Based on this list from Spinup OpenAI.

2018 December:

  • Playing Atari with Deep Reinforcement Learning, Mnih et al, 2013. Algorithm: DQN. paper note
  • Domain Adaptation for reinforcement learning on the atari paper

2019 March:

  • Policy invariance under reward transformations: Theory and application to reward shaping. paper

2019 May:

  • Data-Efficient Hierarchical Reinforcement Learning paper note

2019 June:

  • ICML2015 - Universal Value Function Approximators

2019 July:

  • Deep Reinforcement Learning that matters

2019 Sept:

  • Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
  • Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scences
  • kPAM: KeyPoint Affordances for Category-Level Robotic Manipulation
  • MAT: Multi-fingered adaptive tactile grasping via deep reinforcement learning
  • Self-supervised correspondence in visuomotor policy learning

2019 Nov:

  • Learning to Manipulate Object Collections Using Grounded State Representations (CoRL 2019) [note]
  • Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments (CoRL 2019) [note]

2019 Dec:

  • Playing FPS Games with DRL note
  • Visual Reinforcement Learning with Imagined Goals note
  • Deep Recurrent Q-Learning for POMDPs note

2020 Jan:

  • Deep Q-learning from Demonstrations [note] [paper]
  • Deep Reinforcement Learning with Double Q-Learning [note] paper
  • Dueling Network Architectures for Deep Reinforcement Learning [note] [paper]
  • Learning Latent Plans from Play [note] [paper] [project-site] CoRL2019
  • Time Limit in RL [note] [paper] ICML 2018
  • Multi-model imitation learning in partially observable environments [note] AAMAS 2020 (extended abstract)
  • Learning belieft representations for imitation learning in pomdps [note] [code] Alg: Belief-module imitation learning (BMIL), UAI 2019
  • Learning deep policies for robot bin picking by simulating robust grasping sequences [note] CORL 2017

2020 Aug:

  • Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks a.k.a Cycle GAN [slide]