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Sokoban

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

https://github.com/AbhijeetKrishnan/aml-for-player-modeling

공식 코드

Towards Action Model Learning for Player Modeling

https://github.com/GAIGResearch/LearningFM

공식 코드

Learning Local Forward Models on Unforgiving Games

https://github.com/adaptivesubgoalsearch/adaptive_subs

공식 코드

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search

https://github.com/alignmentresearch/learned-planner

공식 코드

Planning in a recurrent neural network that plays Sokoban

https://github.com/alignmentresearch/train-learned-planner

공식 코드

Planning in a recurrent neural network that plays Sokoban

https://github.com/amidos2006/gym-pcgrl

공식 코드

Tree Search vs Optimization Approaches for Map Generation

https://github.com/amidos2006/marahel

공식 코드

Multi-Objective level generator generation with Marahel

https://github.com/andrewcropper/iggp

공식 코드

Inductive general game playing

https://github.com/andrewcropper/mlj19-iggp

공식 코드

Inductive general game playing

https://github.com/deepmind/boxoban-levels

공식 코드

Single-Agent Policy Tree Search With Guarantees

https://github.com/deepmind/deepmind-research/tree/master/physics_planning_games

공식 코드

Physically Embedded Planning Problems: New Challenges for Reinforcement Learning

https://github.com/deepmind/levintreesearch_cm

공식 코드

Levin Tree Search with Context Models

https://github.com/devaansh100/a_star

공식 코드

A Training Data Recipe to Accelerate A* Search with Language Models

https://github.com/dixantmittal/expose

공식 코드

ExPoSe: Combining State-Based Exploration with Gradient-Based Online Search

https://github.com/facebookresearch/searchformer

공식 코드

Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping

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

공식 코드

Levin Tree Search with Context Models

https://github.com/guicho271828/latplan

공식 코드

Classical Planning in Deep Latent Space

https://github.com/levilelis/h-levin

공식 코드

Policy-Guided Heuristic Search with Guarantees

https://github.com/microsoft/magebench

공식 코드

MageBench: Bridging Large Multimodal Models to Agents

https://github.com/omardelarosa/pcgrl-brush

공식 코드

Mixed-Initiative Level Design with RL Brush

https://github.com/omikad/halfweg

공식 코드

Solving Sokoban using Hierarchical Reinforcement Learning with Landmarks

https://github.com/smearle/control-pcgrl

공식 코드

Illuminating Diverse Neural Cellular Automata for Level Generation

https://github.com/stephen-chung-mh/thinker

공식 코드

Thinker: Learning to Plan and Act

https://github.com/subgoal-search/subgoal-search

공식 코드

Subgoal Search For Complex Reasoning Tasks

https://github.com/sustechgameai/text-to-building-in-minecraft

공식 코드

3D Building Generation in Minecraft via Large Language Models

https://github.com/udg-lai/modref2023

공식 코드

On Grid Graph Reachability and Puzzle Games

https://github.com/yahiaetman/ms-level-gen

공식 코드

Start Small: Training Controllable Game Level Generators without Training Data by Learning at Multiple Sizes

https://github.com/SnDehghani/pcgrl_d_m

Tree Search vs Optimization Approaches for Map Generation

https://github.com/dixantmittal/mctsnet

Learning to Search with MCTSnets

https://github.com/fabiopardo/qmap

Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks

https://github.com/glassices/sokoban_planner

Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning

https://github.com/learningandplanningICLR/learningandplanning

Uncertainty-sensitive Learning and Planning with Ensembles

https://github.com/poi233/pcgrl_rts

Tree Search vs Optimization Approaches for Map Generation

https://github.com/smearle/gym-pcgrl

Tree Search vs Optimization Approaches for Map Generation

https://github.com/yashbonde/chess_lm

Learning to Search with MCTSnets

https://github.com/yl3829/Q-map

Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks

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