Awesome Systems & Control

Key papers

• Synthesizing Decentralized Controllers With Graph Neural Networks And Imitation Learning (2020)
  Fernando Gama, Qingbiao Li, Ekaterina Tolstaya, et al.
  11.08
• CADET: A Modular Platform for Evaluating Distributed Cooperative Autonomy in Connected Autonomous Vehicles (2026)
  Pragya Sharma et al.
  4.39
• For How Long Should We Be Punching? Learning Action Duration in Fighting Games (2026)
  Hoang Hai Nguyen et al.
  4.33
• Progressive Generalization Augmentation with Deeply Coupled RND-PPO and Domain-Prioritized Noise Injection for Robust Crop Management Reinforcement Learning (2026)
  Wu Yang
  2.00
• Adaptive Oscillatory-State Alignment for Time Series Forecasting (2026)
  Zhangyao Song et al.
  2.00
• Pavlovian-Inspired Cue-Outcome Association for Autonomous Agent Navigation (2026)
  M. Saeidi et al.
  2.00
• An Uncertainty-Aware Resilience Micro-Agent for Causal Observability in the Computing Continuum (2026)
  Suvi De Silva et al.
  1.94
• Multi-Agent Temporal Logic Planning via Penalty Functions and Block-Coordinate Optimization (2026)
  Eleftherios E. Vlahakis et al.
  1.78
• Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning (2025)
  Nicol\`o Dal Fabbro et al.
  1.56
• Adaptive Event-Triggered Policy Gradient for Multi-Agent Reinforcement Learning (2025)
  Umer Siddique et al.
  1.50
• OmniRetarget: Interaction-Preserving Data Generation for Humanoid Whole-Body Loco-Manipulation and Scene Interaction (2025)
  Lujie Yang et al.
  1.50
• Decoupled Hierarchical Reinforcement Learning with State Abstraction for Discrete Grids (2025)
  Qingyu Xiao and Yuanlin Chang and Youtian Du
  1.33
• DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty (2025)
  Mingxuan Cui et al.
  1.33
• IKDiffuser: a Diffusion-based Generative Inverse Kinematics Solver for Kinematic Trees (2025)
  Zeyu Zhang et al.
  1.33
• Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series (2025)
  Jiang You et al.
  1.28
• Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization (2025)
  Robbert Reijnen et al.
  1.28
• MIND-Stack: Modular, Interpretable, End-to-End Differentiability for Autonomous Navigation (2025)
  Felix Jahncke et al.
  1.28
• An Real-Sim-Real (RSR) Loop Framework for Generalizable Robotic Policy Transfer with Differentiable Simulation (2025)
  Lu Shi et al.
  1.17
• Towards Constraint-Based Adaptive Hypergraph Learning for Solving Vehicle Routing: An End-to-End Solution (2025)
  Zhenwei Wang et al.
  1.17
• SALE-Based Offline Reinforcement Learning with Ensemble Q-Networks (2025)
  Zheng Chun
  1.06
• Zero-Shot Trajectory Planning for Signal Temporal Logic Tasks (2025)
  Ruijia Liu et al.
  1.06
• G3Flow: Generative 3D Semantic Flow for Pose-aware and Generalizable Object Manipulation (2024)
  Tianxing Chen et al.
  0.94
• Multi-agent assignment via state augmented reinforcement learning (2024)
  Leopoldo Agorio et al.
  0.67
• H2O+: An Improved Framework for Hybrid Offline-and-Online RL with Dynamics Gaps (2023)
  Haoyi Niu et al.
  0.17
• DSSE: a drone swarm search environment (2023)
  Manuel Castanares et al.
  0.06
• Optimal By Design: Model-driven Synthesis Of Adaptation Strategies For Autonomous Systems (2020)
  Yehia Elrakaiby, Paola Spoletini, Bashar Nuseibeh
  0.00
• Action Branching Architectures for Deep Reinforcement Learning (2017)
  Arash Tavakoli et al.
  —
• Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor (2018)
  Tuomas Haarnoja et al.
  —
• Distributed Distributional Deterministic Policy Gradients (2018)
  Gabriel Barth-Maron et al.
  —
• Context-Aware Policy Reuse (2018)
  Siyuan Li et al.
  —
• Adaptive Input Estimation in Linear Dynamical Systems with Applications to Learning-from-Observations (2018)
  Sebastian Curi et al.
  —
• Soft Actor-Critic Algorithms and Applications (2018)
  Tuomas Haarnoja et al.
  —
• Effective Scheduling Function Design in SDN through Deep Reinforcement Learning (2019)
  Huang Victoria et al.
  —
• Control Regularization for Reduced Variance Reinforcement Learning (2019)
  Richard Cheng et al.
  —
• Uncertainty-aware Model-based Policy Optimization (2019)
  Tung-Long Vuong and Kenneth Tran
  —
• Striving for Simplicity and Performance in Off-Policy DRL: Output Normalization and Non-Uniform Sampling (2019)
  Che Wang et al.
  —
• Single Episode Policy Transfer in Reinforcement Learning (2019)
  Jiachen Yang et al.
  —
• Towards More Sample Efficiency in Reinforcement Learning with Data Augmentation (2019)
  Yijiong Lin et al.
  —
• Provably Efficient Model-based Policy Adaptation (2020)
  Yuda Song et al.
  —
• Adaptive Procedural Task Generation for Hard-Exploration Problems (2020)
  Kuan Fang et al.
  —
• Sequential Transfer in Reinforcement Learning with a Generative Model (2020)
  Andrea Tirinzoni et al.
  —
• Learning Event-triggered Control from Data through Joint Optimization (2020)
  Niklas Funk et al.
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• Imitating Unknown Policies via Exploration (2020)
  Nathan Gavenski and Juarez Monteiro and Roger Granada and Felipe Meneguzzi and Rodrigo C. Barros
  —
• An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy Search (2020)
  Kyunghyun Lee et al.
  —
• Synthesizing Decentralized Controllers with Graph Neural Networks and Imitation Learning (2020)
  Fernando Gama et al.
  —
• Learn Dynamic-Aware State Embedding for Transfer Learning (2021)
  Kaige Yang
  —
• Towards Automatic Actor-Critic Solutions to Continuous Control (2021)
  Jake Grigsby et al.
  —
• Towards Exploiting Geometry and Time for Fast Off-Distribution Adaptation in Multi-Task Robot Learning (2021)
  K.R. Zentner et al.
  —
• Generalization of Reinforcement Learning with Policy-Aware Adversarial Data Augmentation (2021)
  Hanping Zhang et al.
  —
• DAAS: Differentiable Architecture and Augmentation Policy Search (2021)
  Xiaoxing Wang et al.
  —
• Evolutionary Action Selection for Gradient-based Policy Learning (2022)
  Yan Ma et al.
  —
• RL-PGO: Reinforcement Learning-based Planar Pose-Graph Optimization (2022)
  Nikolaos Kourtzanidis et al.
  —
• Non-Parametric Stochastic Policy Gradient with Strategic Retreat for Non-Stationary Environment (2022)
  Apan Dastider and Mingjie Lin
  —
• Unsupervised Reinforcement Learning for Transferable Manipulation Skill Discovery (2022)
  Daesol Cho et al.
  —
• Actor Prioritized Experience Replay (2022)
  Baturay Saglam et al.
  —
• Unified State Representation Learning under Data Augmentation (2022)
  Taylor Hearn et al.
  —
• Generative Augmented Flow Networks (2022)
  Ling Pan and Dinghuai Zhang and Aaron Courville and Longbo Huang and Yoshua Bengio
  —
• ControlVAE: Model-Based Learning of Generative Controllers for Physics-Based Characters (2022)
  Heyuan Yao et al.
  —
• Prototypical context-aware dynamics generalization for high-dimensional model-based reinforcement learning (2022)
  Junjie Wang et al.
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• CIM: Constrained Intrinsic Motivation for Sparse-Reward Continuous Control (2022)
  Xiang Zheng et al.
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