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Numerous solutions are proposed for the Traffic Signal Control (TSC) tasks aiming to provide efficient transportation and mitigate congestion waste.
Bert is not a knowledge base (yet): Factual knowledge vs. name-based reasoning in unsupervised qa
Poerner, N.; Waltinger, U.; and Schütze, H. 2019 · 1911
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Colight: Learning network-level cooperation for traffic signal control
Wei, H.; Xu, N.; Zhang, H.; Zheng, G.; Zang, X.; Chen, C.; Zhang, W.; Zhu, Y.; Xu, K.; and Li, Z. 2019b · 1922
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Learning phase competition for traffic signal control
Zheng, G.; Xiong, Y.; Zang, X.; Feng, J.; Wei, H.; Zhang, H.; Li, Y.; Xu, K.; and Li, Z. 2019 · 1972
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A rule-based real-time traffic responsive signal control system with transit priority: application to an isolated intersection
Dion, F.; and Hellinga, B. 2002 · 2002
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Reinforcement learning with multi-fidelity simulators
Cutler, M.; Walsh, T. J.; and How, J. P. 2014 · 2014
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Deep domain confusion: Maximizing for domain invariance. arXiv 2014
Tzeng, E.; Hoffman, J.; Zhang, N.; Saenko, K.; and Darrell, T. 2019 · 2014
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Robots that can adapt like animals
Cully, A.; Clune, J.; Tarapore, D.; and Mouret, J.-B. 2015 · 2015
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Towards adapting deep visuomotor representations from simulated to real environments
Tzeng, E.; Devin, C.; Hoffman, J.; Finn, C.; Peng, X.; Levine, S.; Saenko, K.; and Darrell, T. 2015 · 2015
Earlier work this paper cites.
Grounded action transformation for robot learning in simulation
Hanna, J.; and Stone, P. 2017 · 2017
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Using simulation and domain adaptation to improve efficiency of deep robotic grasping
Bousmalis, K.; Irpan, A.; Wohlhart, P.; Bai, Y.; Kelcey, M.; Kalakrishnan, M.; Downs, L.; Ibarz, J.; Pastor, P.; Konolige, K.; et al. 2018 · 2018
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Multi-task domain adaptation for deep learning of instance grasping from simulation
Fang, K.; Bai, Y.; Hinterstoisser, S.; Savarese, S.; and Kalakrishnan, M. 2018 · 2018
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Microscopic traffic simulation using sumo
Lopez, P. A.; Behrisch, M.; Bieker-Walz, L.; Erdmann, J.; Flötteröd, Y.-P.; Hilbrich, R.; Lücken, L.; Rummel, J.; Wagner, P.; and Wießner, E. 2018 · 2018
Earlier work this paper cites.
Intellilight: A reinforcement learning approach for intelligent traffic light control
Wei, H.; Zheng, G.; Yao, H.; and Li, Z. 2018 · 2018
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Learning transferable features in deep convolutional neural networks for diagnosing unseen machine conditions
Han, T.; Liu, C.; Yang, W.; and Jiang, D. 2019 · 2019
Cited alongside, same era.
Sim-to-real via sim-to-sim: Data-efficient robotic grasping via randomized-to-canonical adaptation networks
James, S.; Wohlhart, P.; Kalakrishnan, M.; Kalashnikov, D.; Irpan, A.; Ibarz, J.; Levine, S.; Hadsell, R.; and Bousmalis, K. 2019 · 2019
Cited alongside, same era.
Language Models as Knowledge Bases?
Petroni, F.; Rocktäschel, T.; Riedel, S.; Lewis, P.; Bakhtin, A.; Wu, Y.; and Miller, A. 2019 · 2019
Cited alongside, same era.
Real-World Robotic Perception and Control Using Synthetic Data
Tobin, J. P. 2019 · 2019
Cited alongside, same era.
Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario
Zhang, H.; Feng, S.; Liu, C.; Ding, Y.; Zhu, Y.; Zhou, Z.; Zhang, W.; Yu, Y.; Jin, H.; and Li, Z. 2019 · 2019
Cited alongside, same era.
Sim-to-real transfer in deep reinforcement learning for robotics: a survey
Zhao, W.; Queralta, J. P.; and Westerlund, T. 2020 · 2020
Later among the works it cites.
Towards real-world deployment of reinforcement learning for traffic signal control
Müller, A.; Rangras, V.; Ferfers, T.; Hufen, F.; Schreckenberg, L.; Jasperneite, J.; Schnittker, G.; Waldmann, M.; Friesen, M.; and Wiering, M. 2021 · 2021
Later among the works it cites.
Flamingo: a visual language model for few-shot learning
Alayrac, J.-B.; Donahue, J.; Luc, P.; Miech, A.; Barr, I.; Hasson, Y.; Lenc, K.; Mensch, A.; Millican, K.; Reynolds, M.; et al. 2022 · 2022
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Using ontology to guide reinforcement learning agents in unseen situations: A traffic signal control system case study
Ghanadbashi, S.; and Golpayegani, F. 2022 · 2022
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LibSignal: An Open Library for Traffic Signal Control
Mei, H.; Lei, X.; Da, L.; Shi, B.; and Wei, H. 2022 · 2022
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Learning dexterous in-hand manipulation
Andrychowicz, O. M.; Baker, B.; Chociej, M.; Jozefowicz, R.; McGrew, B.; Pachocki, J.; Petron, A.; Plappert, M.; Powell, G.; Ray, A.; et al. 2020 · 2020
Cited alongside, same era.
Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control
Chen, C.; Wei, H.; Xu, N.; Zheng, G.; Yang, M.; Xiong, Y.; Xu, K.; and Li, Z. 2020 · 2020
Cited alongside, same era.
Deep reinforcement learning for intelligent transportation systems: A survey
Haydari, A.; and Yılmaz, Y. 2020 · 2020
Cited alongside, same era.
How can we know what language models know?
Jiang, Z.; Xu, F. F.; Araki, J.; and Neubig, G. 2020 · 2020
Cited alongside, same era.
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Shin, T.; Razeghi, Y.; Logan IV, R. L.; Wallace, E.; and Singh, S. 2020 · 2020
Cited alongside, same era.
Multi-agent deep reinforcement learning for urban traffic light control in vehicular networks
Wu, T.; Zhou, P.; Liu, K.; Yuan, Y.; Wang, X.; Huang, H.; and Wu, D. O. 2020 · 2020
Cited alongside, same era.
Metalight: Value-based meta-reinforcement learning for traffic signal control
Zang, X.; Yao, H.; Zheng, G.; Xu, N.; Xu, K.; and Li, Z. 2020 · 2020
Cited alongside, same era.
Reinforcement learning in urban network traffic signal control: A systematic literature review
Noaeen, M.; Naik, A.; Goodman, L.; Crebo, J.; Abrar, T.; Abad, Z. S. H.; Bazzan, A. L.; and Far, B. 2022 · 2022
Later among the works it cites.
Chain-of-thought prompting elicits reasoning in large language models
Wei, J.; Wang, X.; Schuurmans, D.; Bosma, M.; Xia, F.; Chi, E.; Le, Q. V.; Zhou, D.; et al. 2022 · 2022
Later among the works it cites.
Auto-GPT: An Autonomous GPT-4 Experiment
2023 · 2023
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Translations: — BabyAGI
BabyAGI. 2023 · 2023
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Da, L.; Mei, H.; Sharma, R.; and Wei, H. 2023 · 2023
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Deep reinforcement Q-learning for intelligent traffic signal control with partial detection
Ducrocq, R.; and Farhi, N. 2023 · 2023
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LangChian. Introduction — langchain
langchain. 2023 · 2023
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