Alternatives and similar repositories for THICK

Users that are interested in THICK are comparing it to the libraries listed below

• orybkin / lexa
  Discovering and Achieving Goals via World Models, NeurIPS 2021
  ☆86Updated last year
• ahmed-touati / controllable_agent
  ☆52Updated 2 years ago
• ALRhub / MTS3
  Implementation of Neurips 2023 Paper "Multi Time Scale World Models"
  ☆14Updated last year
• seohongpark / METRA
  METRA: Scalable Unsupervised RL with Metric-Aware Abstraction (ICLR 2024)
  ☆81Updated 2 years ago
• dibyaghosh / jaxrl_m
  Skeleton for scalable and flexible Jax RL implementations
  ☆92Updated 2 years ago
• google-deepmind / dmc_vision_benchmark
  ☆30Updated last year
• architsharma97 / earl_benchmark
  EARL: Environment for Autonomous Reinforcement Learning
  ☆37Updated 3 years ago
• kvfrans / fre
  Code for "Unsupervised Zero-Shot RL via Functional Reward Representations"
  ☆57Updated last year
• Lifelong-ML / CompoSuite
  Official release of CompoSuite, a compositional RL benchmark
  ☆50Updated last year
• mazpie / mastering-urlb
  [ICML 2023] Pre-train world model-based agents with different unsupervised strategies, fine-tune the agent's components selectively, and …
  ☆40Updated last year
• RajGhugare19 / alm
  Simplifying Model-based RL: Learning Representations, Latent-space Models and Policies with One Objective
  ☆82Updated 2 years ago
• younggyoseo / apv
  ☆72Updated 3 years ago
• martius-lab / cee-us
  Repository for the paper: "Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation" @ NeurIPS 2022
  ☆20Updated 2 years ago
• SonyResearch / simba
  ☆114Updated 10 months ago
• RajGhugare19 / stitching-is-combinatorial-generalisation
  [ICLR 2024] Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View.
  ☆23Updated last year
• seohongpark / PMA
  Predictable MDP Abstraction for Unsupervised Model-Based RL (ICML 2023)
  ☆32Updated 2 years ago
• seohongpark / HILP
  Foundation Policies with Hilbert Representations (ICML 2024)
  ☆104Updated 3 months ago
• chandar-lab / Recall2Imagine
  Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024
  ☆78Updated last year
• jianlanluo / SAQ
  ☆35Updated 6 months ago
• seohongpark / CSD-locomotion
  Controllability-Aware Unsupervised Skill Discovery (ICML 2023)
  ☆28Updated 2 years ago
• seohongpark / HIQL
  HIQL: Offline Goal-Conditioned RL with Latent States as Actions (NeurIPS 2023)
  ☆92Updated last year
• suyoung-lee / LDM
  Latent Dynamics Mixture, NeurIPS 2021
  ☆18Updated 3 years ago
• jurgisp / memory-maze
  Evaluating long-term memory of reinforcement learning algorithms
  ☆160Updated 2 years ago
• mazpie / choreographer
  [ICLR 2023] Choreographer: a world-model-based agent that discovers and learns unsupervised skills in latent imagination, and it's able t…
  ☆41Updated last year
• fdeng18 / dreamer-pro
  ☆36Updated 3 years ago
• schmidtdominik / LAPO
  Code for the ICLR 2024 spotlight paper: "Learning to Act without Actions" (introducing Latent Action Policies)
  ☆131Updated last year
• martius-lab / SMORL
  ☆22Updated 3 years ago
• penn-pal-lab / peg
  Code for "Planning Goals for Exploration", ICLR2023 Spotlight. An unsupervised RL agent for hard exploration tasks.
  ☆81Updated last year
• namsan96 / SiMPL
  ☆48Updated 2 years ago
• scottemmons / rvs
  Reinforcement Learning via Supervised Learning
  ☆72Updated 3 years ago