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How Well Do Reinforcement Learning Approaches Cope With Disruptions? The Case of Traffic Signal Control
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Principal Component Analysis
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The Science and Practice of Resilience
inferredcites →https://doi.org/10.1007/978-3-030-36841-8_22openalex-snapshot
State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability
inferredcites →https://doi.org/10.1007/978-3-540-74089-6_7openalex-snapshot
An Agent-Based Approach to Self-organized Production
inferredcites →https://doi.org/10.1007/978-3-540-87479-9_61openalex-snapshot
Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs
inferredcites →https://doi.org/10.1007/s11116-017-9814-yopenalex-snapshot
The role of travel demand and network centrality on the connectivity and resilience of an urban street system
inferredcites →https://doi.org/10.1016/0191-2615(91)90013-9openalex-snapshot
A multi-band approach to arterial traffic signal optimization
inferredcites →https://doi.org/10.1016/0893-6080(89)90020-8openalex-snapshot
Multilayer feedforward networks are universal approximators
inferredcites →https://doi.org/10.1016/j.comcom.2020.02.069openalex-snapshot
Applications of Artificial Intelligence and Machine learning in smart cities
inferredcites →https://doi.org/10.1016/j.future.2019.04.017openalex-snapshot
Machine learning in the Internet of Things: Designed techniques for smart cities
inferredcites →https://doi.org/10.1016/j.physa.2006.01.047openalex-snapshot
Decentralised control of material or traffic flows in networks using phase-synchronisation
inferredcites →https://doi.org/10.1016/j.ress.2021.107926openalex-snapshot
Infrastructure resilience curves: Performance measures and summary metrics
inferredcites →https://doi.org/10.1038/nature14236openalex-snapshot
Human-level control through deep reinforcement learning
inferredcites →https://doi.org/10.1038/s41598-022-21125-3openalex-snapshot
Adaptability and sustainability of machine learning approaches to traffic signal control
inferredcites →https://doi.org/10.1080/00139157.2013.768076openalex-snapshot
Disaster Resilience: A National Imperative
inferredcites →https://doi.org/10.1088/1742-5468/2008/04/p04019openalex-snapshot
Self-control of traffic lights and vehicle flows in urban road networks
inferredcites →https://doi.org/10.1103/physreve.70.066116openalex-snapshot
Physics, stability, and dynamics of supply networks
inferredcites →https://doi.org/10.1109/access.2014.2325029openalex-snapshot
Big Data Deep Learning: Challenges and Perspectives
inferredcites →https://doi.org/10.1109/access.2022.3204057openalex-snapshot
Analytically Guided Reinforcement Learning for Green It and Fluent Traffic
inferredcites →https://doi.org/10.1109/ijcnn.2012.6252852openalex-snapshot
Traffic signal optimization using Ant Colony Algorithm
inferredcites →https://doi.org/10.1109/itsc.2013.6728480openalex-snapshot
Towards distributed online cooperative traffic signal control using the cell transmission model
inferredcites →https://doi.org/10.1109/mci.2010.938363openalex-snapshot
Multi-Agent System in Urban Traffic Signal Control
inferredcites →https://doi.org/10.1109/robot.2010.5509621openalex-snapshot
Superhuman performance of surgical tasks by robots using iterative learning from human-guided demonstrations
inferredcites →https://doi.org/10.1109/tits.2013.2255286openalex-snapshot
Multiagent Reinforcement Learning for Integrated Network of Adaptive Traffic Signal Controllers (MARLIN-ATSC): Methodology and Large-Scale Application on Downtown Toronto
inferredcites →https://doi.org/10.1109/tits.2022.3208236openalex-snapshot
Congested Urban Networks Tend to Be Insensitive to Signal Settings: Implications for Learning-Based Control
inferredcites →https://doi.org/10.1109/tnn.1998.712192openalex-snapshot
Reinforcement Learning: An Introduction
inferredcites →https://doi.org/10.1109/tsmcc.2007.913919openalex-snapshot
A Comprehensive Survey of Multiagent Reinforcement Learning
inferredcites →https://doi.org/10.1126/sciadv.1701079openalex-snapshot
Resilience and efficiency in transportation networks
inferredcites →https://doi.org/10.1126/sciadv.aba2423openalex-snapshot
When floods hit the road: Resilience to flood-related traffic disruption in the San Francisco Bay Area and beyond
inferredcites →https://doi.org/10.1126/science.aar6404openalex-snapshot
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
inferredcites →https://doi.org/10.1145/3308558.3314139openalex-snapshot
CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
inferredcites →https://doi.org/10.1145/3340531.3411859openalex-snapshot
GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning
inferredcites →https://doi.org/10.1155/2018/1096123openalex-snapshot
A Review of the Self-Adaptive Traffic Signal Control System Based on Future Traffic Environment
inferredcites →https://doi.org/10.1287/opre.14.4.568openalex-snapshot
The Synchronization of Traffic Signals by Mixed-Integer Linear Programming
inferredcites →https://doi.org/10.14441/eier.d2013002openalex-snapshot
Economics 2.0: The Natural Step towards a Self-Regulating, Participatory Market Society
inferredcites →https://doi.org/10.1512/iumj.1957.6.56038openalex-snapshot
A Markovian Decision Process
inferredcites →https://doi.org/10.1609/aaai.v30i1.10295openalex-snapshot
Deep Reinforcement Learning with Double Q-Learning
inferredcites →https://doi.org/10.1609/aaai.v34i01.5467openalex-snapshot
MetaLight: Value-Based Meta-Reinforcement Learning for Traffic Signal Control
inferredcites →https://doi.org/10.25088/complexsystems.16.1.29openalex-snapshot
Self-organizing Traffic Lights
inferredcites →https://doi.org/10.3929/ethz-b-000456701openalex-snapshot
Wirkungsanalyse Selbst-Steuerung
inferredcites →https://doi.org/10.48550/arxiv.1804.06893openalex-snapshot
A Study on Overfitting in Deep Reinforcement Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4598461openalex-extracted
Democratizing Traffic Control in Smart Cities
inferred← citeshttps://doi.org/10.1007/978-981-95-9101-5_40openalex-snapshot
Enhancing Urban Mobility Modeling, Privacy, and Efficiency Through Machine-Learning Algorithm
inferred← citeshttps://doi.org/10.1016/j.rineng.2026.109771openalex-snapshot
EcoEdge-traffic: A lightweight edge-based reinforcement model for green urban mobility
inferred← citeshttps://doi.org/10.1016/j.trc.2024.104511openalex-snapshot
Democratizing traffic control in smart cities
inferred← citeshttps://doi.org/10.1016/j.trip.2025.101618openalex-snapshot
Mycomobility: Analysis of human transport through a mycorrhizal analogy
inferred← citeshttps://doi.org/10.1080/12265934.2025.2586754openalex-snapshot
Optimal traffic signal control for an atypical isolated intersection using composite AI model
inferred← citeshttps://doi.org/10.3390/app142411952openalex-snapshot
Spatial Performance Indicators for Traffic Flow Prediction
inferred← citeshttps://doi.org/10.3390/e25070982openalex-snapshot
Deep Reinforcement Meta-Learning and Self-Organization in Complex Systems: Applications to Traffic Signal Control
inferred← citeshttps://doi.org/10.5220/0012699200003702openalex-snapshot
Spatial Performance Indicators to Evaluate Spatiotemporal Traffic Prediction
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