Cover Image

A Parallel Hybrid Action Space Reinforcement Learning Model for Real-world Adaptive Traffic Signal Control

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Yuxuan, Long, Meng, Wu, Qiang, Liu, Wei, Pi, Jiatian, Yang, Xinmin
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence I.2.6; I.2.8
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
by: Yousaf, Iqra
Published: (2024)

From Cumulative Constraints to Adaptive Runtime Safety Control for Nonstationary Reinforcement Learning
by: Tomashevskiy, Timofey
Published: (2026)

Predicting Future Actions of Reinforcement Learning Agents
by: Chung, Stephen, et al.
Published: (2024)

Sketch Decompositions for Classical Planning via Deep Reinforcement Learning
by: Aichmüller, Michael, et al.
Published: (2024)

Fractional Policy Gradients: Reinforcement Learning with Long-Term Memory
by: Pawar, Urvi, et al.
Published: (2025)

Selective Progress-Aware Querying for Human-in-the-Loop Reinforcement Learning
by: Muraleedharan, Anujith, et al.
Published: (2025)

Zero-Shot Context Generalization in Reinforcement Learning from Few Training Contexts
by: Chapman, James, et al.
Published: (2025)

FlowRL: Flow-Augmented Few-Shot Reinforcement Learning for Semi-Structured Sensor Data
by: Pivezhandi, Mohammad, et al.
Published: (2024)

Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
by: Silue, Bram, et al.
Published: (2025)

GIRL: Generative Imagination Reinforcement Learning via Information-Theoretic Hallucination Control
by: Hiremath, Prakul Sunil
Published: (2026)

LeanProgress: Guiding Search for Neural Theorem Proving via Proof Progress Prediction
by: George, Robert Joseph, et al.
Published: (2025)

Predicting and improving test-time scaling laws via reward tail-guided search
by: Li, Muheng, et al.
Published: (2026)

NeSIG: A Neuro-Symbolic Method for Learning to Generate Planning Problems
by: Núñez-Molina, Carlos, et al.
Published: (2023)

Constrained Auto-Bidding via Generative Response Modeling
by: Yang, Eunseok, et al.
Published: (2026)

Learning to Select Goals in Automated Planning with Deep-Q Learning
by: Núñez-Molina, Carlos, et al.
Published: (2024)

Foundational Requirements for Artificial General Intelligence: A Falsifiable Framework Based on Signal Prediction
by: Šprogar, Matej
Published: (2025)

An Aircraft Upset Recovery System with Reinforcement Learning
by: Demir, Mahir, et al.
Published: (2026)

Sim-to-reality adaptation for Deep Reinforcement Learning applied to an underwater docking application
by: Chaarani, Alaaeddine, et al.
Published: (2026)

Safe Reinforcement Learning with Preference-based Constraint Inference
by: Li, Chenglin, et al.
Published: (2026)

Resolving Action Bottleneck: Agentic Reinforcement Learning Informed by Token-Level Energy
by: He, Langzhou, et al.
Published: (2026)

CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning
by: Sauter, Andreas W. M., et al.
Published: (2024)

Actor-Critic Model Predictive Control: Differentiable Optimization meets Reinforcement Learning for Agile Flight
by: Romero, Angel, et al.
Published: (2023)

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
by: Zawalski, Michał, et al.
Published: (2022)

StepScorer: Accelerating Reinforcement Learning with Step-wise Scoring and Psychological Regret Modeling
by: Xu, Zhe
Published: (2026)

A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making
by: Núñez-Molina, Carlos, et al.
Published: (2023)

Deep Reinforcement Learning for Day-to-day Dynamic Tolling in Tradable Credit Schemes
by: Wu, Xiaoyi, et al.
Published: (2025)

Umbrella Reinforcement Learning -- computationally efficient tool for hard non-linear problems
by: Nuzhin, Egor E., et al.
Published: (2024)

SMOSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks
by: Vincze, Mátyás, et al.
Published: (2024)

Reward-Modulated Local Learning in Spiking Encoders: Controlled Benchmarks with STDP and Hybrid Rate Readouts
by: Chakraborty, Debjyoti
Published: (2026)

Incentives for Responsiveness, Instrumental Control and Impact
by: Carey, Ryan, et al.
Published: (2020)

Joint Combinatorial Node Selection and Resource Allocations in the Lightning Network using Attention-based Reinforcement Learning
by: Salahshour, Mahdi, et al.
Published: (2024)

Procedural Game Level Design with Deep Reinforcement Learning
by: Özkan, Miraç Buğra
Published: (2025)

APC-GNN++: An Adaptive Patient-Centric GNN with Context-Aware Attention and Mini-Graph Explainability for Diabetes Classification
by: Berkani, Khaled
Published: (2025)

The Final-Stage Bottleneck: A Systematic Dissection of the R-Learner for Network Causal Inference
by: Sairam, S, et al.
Published: (2025)

From Next Token Prediction to (STRIPS) World Models
by: Núñez-Molina, Carlos, et al.
Published: (2025)

PIRS: Physics-Informed Reward Shaping for SAC-Based Building Energy Management
by: Zaregarizi, Shadmehr, et al.
Published: (2026)

Are We Winning the Wrong Game? Revisiting Evaluation Practices for Long-Term Time Series Forecasting
by: Phungtua-eng, Thanapol, et al.
Published: (2026)

PillagerBench: Benchmarking LLM-Based Agents in Competitive Minecraft Team Environments
by: Schipper, Olivier, et al.
Published: (2025)

Improving Industrial Injection Molding Processes with Explainable AI for Quality Classification
by: Rottenwalter, Georg, et al.
Published: (2025)

Novel Approaches to Artificial Intelligence Development Based on the Nearest Neighbor Method
by: Priezzhev, I. I., et al.
Published: (2025)