Topic: deep-rl Goto Github
Some thing interesting about deep-rl
Some thing interesting about deep-rl
deep-rl,Deep Q-Learning algorithms to solve LunarLander-v2.
User: albjerto
deep-rl,You can see a reference for Books, Articles, Courses and Educational Materials in this field. Implementation of Reinforcement Learning Algorithms and Environments. Python, OpenAI Gym, Tensorflow.
User: aminkhani
Home Page: https://github.com/aminkhani/Deep-RL
deep-rl,An application of Reinforcement Learning (RL) from the SDD RL class to function approximators and deep learning.
User: amtoine
deep-rl,⚡️ Code and Notes 📝 for Grokking Deep RL and RL: An Introduction by Sutton & Barto(2nd edition, 2018) 🤘
User: ashutoshtiwari13
deep-rl,VR-Caps: A Virtual Environment for Active Capsule Endoscopy
User: capsuleendoscope
Home Page: https://www.youtube.com/watch?v=UQ2u3CIUciA
deep-rl,Recall 2 Imagine, a World Model with superhuman memory. Oral (1.2%) @ ICLR 2024
Organization: chandar-lab
Home Page: https://recall2imagine.github.io/
deep-rl,Deep Reinforcement Learning framework based on TensorFlow and OpenAI Gym
User: dbobrenko
deep-rl,Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"
User: devendrachaplot
Home Page: http://www.cs.cmu.edu/~dchaplot/projects/neural-slam.html
deep-rl,Pytorch code for NeurIPS-20 Paper "Object Goal Navigation using Goal-Oriented Semantic Exploration"
User: devendrachaplot
Home Page: https://devendrachaplot.github.io/projects/semantic-exploration
deep-rl,Simple PyTorch implementation of the Vanilla Policy Gradient algorithm.
User: ebrahimpichka
deep-rl,Accelerated minigrid environments with JAX
User: epignatelli
deep-rl,DRLA-eTGM
User: feiyuyangaioptimplanning
deep-rl,Yet another deep reinforcement learning
User: gbartyzel
deep-rl,:sparkles: A plotter for reinforcement learning (RL)
User: gxywy
deep-rl,Code for NeurIPS 2023 paper Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
User: holarissun
Home Page: https://arxiv.org/pdf/2310.07747.pdf
deep-rl,Simple DQN implementation in jupyter notebook
User: ishanshukla97
deep-rl,A general model-free off-policy actor-critic implementation. Continuous and Discrete Soft Actor-Critic with multimodal observations, data augmentation, offline learning and behavioral cloning.
User: jakegrigsby
deep-rl,My solution to the NeurIPS challenge Learn to Move: Walk Around
User: kamenbliznashki
deep-rl,This repository implements the use of AI for robot tasks.
User: kanishknavale
deep-rl,A curated list of awesome Deep Reinforcement Learning resources.
User: kengz
deep-rl,Attend Before you Act: Leveraging human visual attention for continual learning
User: kkhetarpal
Home Page: https://sites.google.com/view/attendbeforeyouact
deep-rl,Code repository with classical reinforcement learning and deep reinforcement learning methods for Pokémon battles in Pokémon Showdown.
User: leolellisr
Home Page: https://github.com/leolellisr/poke_RL
deep-rl,DeepTraffic is a deep reinforcement learning competition, part of the MIT Deep Learning series.
User: lexfridman
Home Page: https://selfdrivingcars.mit.edu/deeptraffic
deep-rl,Tutorials, assignments, and competitions for MIT Deep Learning related courses.
User: lexfridman
Home Page: https://deeplearning.mit.edu
deep-rl,RLbox: Solving OpenAI Gym with TensorFlow
User: lgvaz
deep-rl,Mirror Descent Policy Optimization
User: manantomar
deep-rl,CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
User: mishalaskin
deep-rl,Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning
Organization: nus-lid
Home Page: https://arxiv.org/abs/2107.01904
deep-rl,A curated list of awesome intelligent autonomous systems ecosystem
User: reza-ebrahimi
deep-rl,$GME Trading using Deep Reinforcement Learning algorithms
User: tsaousis
deep-rl,Exploration of deep reinforcement learning and various state-of-the-art techniques to create a turely autonomous agent.
User: victor-iyi
deep-rl,Implementation of Curiosity-Driven Exploration with PyTorch
User: yangyangii
deep-rl,Codes accompanying the paper "Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning" (NeurIPS 2021 Spotlight https://arxiv.org/abs/2106.03400)
User: yiqinyang
deep-rl,Demos of deep RL algorithms.
User: zhihanyang2022
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