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https://doi.org/10.2139/ssrn.4566668

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/net.21868openalex-extracted
Minimum‐risk routing through a mapped minefield
inferredcites →https://doi.org/10.1007/978-3-030-95470-3_23openalex-extracted
Modular Networks Prevent Catastrophic Interference in Model-Based Multi-task Reinforcement Learning
inferredcites →https://doi.org/10.1007/s00773-010-0089-7openalex-extracted
Collision risk assessment for ships
inferredcites →https://doi.org/10.1016/j.apor.2021.102759openalex-extracted
A path planning strategy unified with a COLREGS collision avoidance function based on deep reinforcement learning and artificial potential field
inferredcites →https://doi.org/10.1016/j.ifacol.2016.10.344openalex-extracted
A Reactive COLREGs-Compliant Navigation Strategy for Autonomous Maritime Navigation
inferredcites →https://doi.org/10.1016/j.ins.2022.01.035openalex-extracted
Adaptively sharing multi-levels of distributed representations in multi-task learning
inferredcites →https://doi.org/10.1016/j.neucom.2021.09.071openalex-extracted
Path planning and dynamic collision avoidance algorithm under COLREGs via deep reinforcement learning
inferredcites →https://doi.org/10.1016/j.oceaneng.2019.106299openalex-extracted
A knowledge-free path planning approach for smart ships based on reinforcement learning
inferredcites →https://doi.org/10.1016/j.oceaneng.2019.106436openalex-extracted
COLREGs-compliant multiship collision avoidance based on deep reinforcement learning
inferredcites →https://doi.org/10.1016/j.oceaneng.2019.106766openalex-extracted
Energy efficient path planning for Unmanned Surface Vehicle in spatially-temporally variant environment
inferredcites →https://doi.org/10.1016/j.oceaneng.2020.107001openalex-extracted
Collision avoidance for an unmanned surface vehicle using deep reinforcement learning
inferredcites →https://doi.org/10.1016/j.oceaneng.2020.107910openalex-extracted
A collision avoidance decision-making system for autonomous ship based on modified velocity obstacle method
inferredcites →https://doi.org/10.1016/j.oceaneng.2021.108612openalex-extracted
Cooperative collision avoidance for unmanned surface vehicles based on improved genetic algorithm
inferredcites →https://doi.org/10.1016/j.oceaneng.2021.109216openalex-extracted
Deep reinforcement learning-based collision avoidance for an autonomous ship
inferredcites →https://doi.org/10.1016/j.oceaneng.2021.109380openalex-extracted
Collision-avoidance navigation systems for Maritime Autonomous Surface Ships: A state of the art survey
inferredcites →https://doi.org/10.1016/j.oceaneng.2021.110166openalex-extracted
Obstacle avoidance strategy for an autonomous surface vessel based on modified deep deterministic policy gradient
inferredcites →https://doi.org/10.1016/j.oceaneng.2022.110749openalex-extracted
COLREGs-abiding hybrid collision avoidance algorithm based on deep reinforcement learning for USVs
inferredcites →https://doi.org/10.1016/j.oceaneng.2022.110772openalex-extracted
A quasi-reflection based SC-PSO for ship path planning with grounding avoidance
inferredcites →https://doi.org/10.1016/j.promfg.2020.02.019openalex-extracted
Towards Shipping 4.0. A preliminary gap analysis
inferredcites →https://doi.org/10.1080/25725084.2019.1707938openalex-extracted
The IMO initial strategy for reducing Greenhouse Gas(GHG) emissions, and its follow-up actions towards 2050
inferredcites →https://doi.org/10.1109/access.2020.3022600openalex-extracted
COLREG-Compliant Collision Avoidance for Unmanned Surface Vehicle Using Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/smc42975.2020.9283219openalex-extracted
A Tripartite Theory of Trustworthiness for Autonomous Systems
inferredcites →https://doi.org/10.1109/tits.2021.3054625openalex-extracted
Deep Reinforcement Learning for Autonomous Driving: A Survey
inferredcites →https://doi.org/10.1109/tsmc.2021.3098451openalex-extracted
Proximal Policy Optimization With Policy Feedback
inferredcites →https://doi.org/10.1155/2021/7765130openalex-extracted
An Optimized Path Planning Method for Coastal Ships Based on Improved DDPG and DP
inferredcites →https://doi.org/10.1609/aaai.v34i05.6424openalex-extracted
Learning Sparse Sharing Architectures for Multiple Tasks
inferredcites →https://doi.org/10.3390/jmse10010003openalex-extracted
An Efficient Ship Automatic Collision Avoidance Method Based on Modified Artificial Potential Field
inferredcites →https://doi.org/10.3390/jmse8110852openalex-extracted
A Comparative Assessment of Collision Risk of Manned and Unmanned Vessels
inferredcites →https://doi.org/10.48550/arxiv.1911.05034openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2005.12729openalex-extracted
Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO
inferredcites →https://doi.org/10.48550/arxiv.2006.09540openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2009.04416openalex-extracted
Phasic Policy Gradient
inferredcites →https://doi.org/10.48550/arxiv.2401.09561openalex-extracted
Sharing Knowledge in Multi-Task Deep Reinforcement Learning
inferredcites →https://doi.org/10.6119/jmst.201904_27(2).0003openalex-extracted
AN AUTOMATIC COLLISION AVOIDANCE AND ROUTE GENERATING ALGORITHM FOR SHIPS BASED ON FIELD MODEL

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inferred← citeshttps://doi.org/10.33815/2313-4763.2023.1-2.26-27.144-165openalex-snapshot
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