https://github.com/RyanNavillus/Syllabus
공식 코드Syllabus: Portable Curricula for Reinforcement Learning Agents
Papers with Code 아카이브
NetHack
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Mean in-game score over 1000 episodes with random seeds not seen during training. See https://arxiv.org/abs/2006.13760 (Section 2.4 Evaluation Protocol) for details.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/agi-labs/continual_rl
공식 코드CORA: Benchmarks, Baselines, and Metrics as a Platform for Continual Reinforcement Learning Agents
https://github.com/allenai/sso
공식 코드Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
https://github.com/bartekcupial/finetuning-rl-as-cl
공식 코드Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
https://github.com/commandercero/netplay
공식 코드Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents
https://github.com/corl-team/katakomba
공식 코드https://github.com/facebookresearch/minihack
공식 코드MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research
https://github.com/facebookresearch/motif
공식 코드Motif: Intrinsic Motivation from Artificial Intelligence Feedback
https://github.com/facebookresearch/nle
공식 코드https://github.com/facebookresearch/oni
공식 코드Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback
https://github.com/michaeltmatthews/craftax
공식 코드Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
https://github.com/pervasive-ai-lab/luckymera
공식 코드LuckyMera: a Modular AI Framework for Building Hybrid NetHack Agents
https://github.com/princeton-nlp/il-scaling-in-games
공식 코드https://github.com/ucl-dark/skillhack
공식 코드Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning
https://github.com/upiterbarg/diff_history
공식 코드https://github.com/vzhong/language-dynamics-distillation
공식 코드Improving Policy Learning via Language Dynamics Distillation
https://github.com/vzhong/silg
공식 코드SILG: The Multi-environment Symbolic Interactive Language Grounding Benchmark
https://github.com/Pieter-Cawood/Reinforcement-Learning
https://github.com/Sarah-wookey/RL_NetHack_2020
https://github.com/dllllb/neurips2021-nethack-raph
https://github.com/emerge-lab/gpudrive
PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice
https://github.com/tianjunz/NovelD
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.