Papers with Code 아카이브

Sequential Decision Making

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 0
보존된 평가 기록: 0

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/coreylowman/synthesis

Thinking Fast and Slow with Deep Learning and Tree Search

https://github.com/debjitpaul/refiner

Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

https://github.com/edmundmills/basalt-competition

IQ-Learn: Inverse soft-Q Learning for Imitation

https://github.com/epfl-imos/sym-q

Sym-Q: Adaptive Symbolic Regression via Sequential Decision-Making

https://github.com/evangravelle/AI-projects

Thinking Fast and Slow with Deep Learning and Tree Search

https://github.com/facebookresearch/Horizon

Doubly Robust Off-policy Value Evaluation for Reinforcement Learning

https://github.com/facebookresearch/ReAgent

Doubly Robust Off-policy Value Evaluation for Reinforcement Learning

https://github.com/facebookresearch/minihack

Generalization to New Sequential Decision Making Tasks with In-Context Learning

https://github.com/gammatauai/leetcode-hard-gym

Reflexion: Language Agents with Verbal Reinforcement Learning

https://github.com/geekJZY/arcticnet

SkipNet: Learning Dynamic Routing in Convolutional Networks

https://github.com/google-deepmind/csil

IQ-Learn: Inverse soft-Q Learning for Imitation

https://github.com/grayswanai/nanogcg

An Alternative Softmax Operator for Reinforcement Learning

https://github.com/h-j-han/automatic_explicitation

Quizbowl: The Case for Incremental Question Answering

https://github.com/idthanm/mpg

Mixed Policy Gradient: off-policy reinforcement learning driven jointly by data and model

https://github.com/illidanlab/sail

Learning Sparse Rewarded Tasks from Sub-Optimal Demonstrations

https://github.com/imagination-research/lbt

Reflexion: Language Agents with Verbal Reinforcement Learning

https://github.com/irskid5/drr_restaurants

Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling

https://github.com/jaara/classification-with-costly-features

Classification with Costly Features as a Sequential Decision-Making Problem

https://github.com/jhejna/dwsl

Distance Weighted Supervised Learning for Offline Interaction Data

https://github.com/keras-team/keras-io/blob/master/examples/vision/temporal_latent_bottleneck.py

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning

https://github.com/kjboggess/ijcai23

Toward Policy Explanations for Multi-Agent Reinforcement Learning

https://github.com/knowledgetechnologyuhh/goal_conditioned_RL_baselines

Learning Multi-Level Hierarchies with Hindsight

https://github.com/lucylow/Covid_Control

Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription

https://github.com/mahaitongdae/safety_index_synthesis

Mixed Policy Gradient: off-policy reinforcement learning driven jointly by data and model

https://github.com/michaelwan11/MIKT

Mutual Information Based Knowledge Transfer Under State-Action Dimension Mismatch

https://github.com/microsoft/llf-bench

LLF-Bench: Benchmark for Interactive Learning from Language Feedback

https://github.com/mila-iqia/ddxplus

Efficient Symptom Inquiring and Diagnosis via Adaptive Alignment of Reinforcement Learning and Classification

https://github.com/miralab-ustc/rl-spf

Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?

https://github.com/mlisicki/neuralkernelbandits

Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling

https://github.com/n9839950/EGH400-2-DSN

Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

https://github.com/neda60/video-summarization-using-FCSN

Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

https://github.com/nikhilbarhate99/Hierarchical-Actor-Critic-HAC-PyTorch

Learning Multi-Level Hierarchies with Hindsight

https://github.com/nikonkate/DQBirds

Deep Q-Network for Angry Birds

https://github.com/noahshinn/reflexion

Reflexion: Language Agents with Verbal Reinforcement Learning

https://github.com/obster991/RL-model-based-planning-from-scratch

Learning model-based planning from scratch

https://github.com/phixion/phixion

Reinforcement Learning: An Overview

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.