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Reinforcement Learning

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코드

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

https://github.com/fdeng18/dreamer-pro

공식 코드

DreamerPro: Reconstruction-Free Model-Based Reinforcement Learning with Prototypical Representations

https://github.com/fdojurado/pynetsim

공식 코드

LEACH-RLC: Enhancing IoT Data Transmission with Optimized Clustering and Reinforcement Learning

https://github.com/fengxiaoming520/rlministyler

공식 코드

RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation

https://github.com/fernandodemeer/rl_optimal_execution

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A Modular Framework for Reinforcement Learning Optimal Execution

https://github.com/ferretdoll/hgr

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Hologram Reasoning for Solving Algebra Problems with Geometry Diagrams

https://github.com/fietelab/farcuriosity

공식 코드

Neuro-Inspired Fragmentation and Recall to Overcome Catastrophic Forgetting in Curiosity

https://github.com/filangel/qtrader

공식 코드

Reinforcement Learning for Portfolio Management

https://github.com/filangelos/social_rl

공식 코드

PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning

https://github.com/filippoairaldi/mpcrl-cbf

공식 코드

Probabilistically safe and efficient model-based Reinforcement Learning

https://github.com/filippoairaldi/mpcrl-for-ramp-metering

공식 코드

Reinforcement Learning with Model Predictive Control for Highway Ramp Metering

https://github.com/financialcomputingucl/drl_for_active_high_frequency_trading

공식 코드

Deep Reinforcement Learning for Active High Frequency Trading

https://github.com/fineartz/dydiff

공식 코드

Long-Horizon Rollout via Dynamics Diffusion for Offline Reinforcement Learning

https://github.com/flairox/cultural-accumulation

공식 코드

Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning

https://github.com/flennerhag/warpgrad

공식 코드

Meta-Learning with Warped Gradient Descent

https://github.com/flexi-framework/drl_les

공식 코드

Deep Reinforcement Learning for Turbulence Modeling in Large Eddy Simulations

https://github.com/flexi-framework/relexi

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Deep Reinforcement Learning for Computational Fluid Dynamics on HPC Systems

https://github.com/flint-xf-fan/Byzantine-Federeated-RL

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Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee

https://github.com/florensacc/snn4hrl

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Stochastic Neural Networks for Hierarchical Reinforcement Learning

https://github.com/florentdelgrange/wae_mdp

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Wasserstein Auto-encoded MDPs: Formal Verification of Efficiently Distilled RL Policies with Many-sided Guarantees

https://github.com/floringogianu/snrl

공식 코드

Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective

https://github.com/flow-project/flow

공식 코드

Flow: A Modular Learning Framework for Mixed Autonomy Traffic

https://github.com/flowersteam/EpidemiOptim

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EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models

https://github.com/flowersteam/Imagine

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Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven Exploration

https://github.com/flowersteam/TeachMyAgent

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TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL

https://github.com/flowersteam/curious

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CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning

https://github.com/flowersteam/geppg

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GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms

https://github.com/flowersteam/playground_env

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Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven Exploration

https://github.com/flowersteam/rl-difference-testing

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How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments

https://github.com/flowersteam/rl_stats

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A Hitchhiker's Guide to Statistical Comparisons of Reinforcement Learning Algorithms

https://github.com/flowersteam/teachDeepRL

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Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments

https://github.com/flowss/rlmutation

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Mutation Testing of Deep Reinforcement Learning Based on Real Faults

https://github.com/flxclxc/rl-graph-search

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Reinforcement Learning Discovers Efficient Decentralized Graph Path Search Strategies

https://github.com/flyao123/district-microgrid-dataset

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A Holistic Power Optimization Approach for Microgrid Control Based on Deep Reinforcement Learning

https://github.com/fmaxgarcia/Meta-MDP

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A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning

https://github.com/fmorenovr/DRDQ-Atari

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Performing Deep Recurrent Double Q-Learning for Atari Games

https://github.com/fmpr/CAREL

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Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures

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