Reinforcement learning with guarantees: a review
Reinforcement learning is concerned with a generic concept of an agent acting in an
environment. From the control theory standpoint, reinforcement learning may be considered …
environment. From the control theory standpoint, reinforcement learning may be considered …
[PDF][PDF] Dynamic potential-based reward sha**
Potential-based reward sha** can significantly improve the time needed to learn an
optimal policy and, in multiagent systems, the performance of the final joint-policy. It has …
optimal policy and, in multiagent systems, the performance of the final joint-policy. It has …
Reward sha** in episodic reinforcement learning
M Grzes - 2017 - kar.kent.ac.uk
Recent advancements in reinforcement learning confirm that reinforcement learning
techniques can solve large scale problems leading to high quality autonomous decision …
techniques can solve large scale problems leading to high quality autonomous decision …
[КНИГА][B] Multi-agent machine learning: A reinforcement approach
HM Schwartz - 2014 - books.google.com
The book begins with a chapter on traditional methods of supervised learning, covering
recursive least squares learning, mean square error methods, and stochastic approximation …
recursive least squares learning, mean square error methods, and stochastic approximation …
Graph convolutional recurrent networks for reward sha** in reinforcement learning
In this paper, we consider the problem of low-speed convergence in Reinforcement
Learning (RL). As a solution, various potential-based reward sha** techniques were …
Learning (RL). As a solution, various potential-based reward sha** techniques were …
Temporal-logic-based reward sha** for continuing reinforcement learning tasks
In continuing tasks, average-reward reinforcement learning may be a more appropriate
problem formulation than the more common discounted reward formulation. As usual …
problem formulation than the more common discounted reward formulation. As usual …
Optimizing anti-collision strategy for MASS: A safe reinforcement learning approach to improve maritime traffic safety
Maritime autonomous surface ships (MASS) promise enhanced efficiency, reduced human
errors, and to improve maritime traffic safety. However, MASS navigation in complex …
errors, and to improve maritime traffic safety. However, MASS navigation in complex …
[HTML][HTML] Exploring three pillars of construction robotics via dual-track quantitative analysis
Y Liu, AHB Alias, NA Haron, NA Bakar… - Automation in …, 2024 - Elsevier
Construction robotics has emerged as a leading technology in the construction industry. This
paper conducts an innovative dual-track quantitative comprehensive method to analyze the …
paper conducts an innovative dual-track quantitative comprehensive method to analyze the …
COLERGs-constrained safe reinforcement learning for realising MASS's risk-informed collision avoidance decision making
Maritime autonomous surface ship (MASS) represents a significant advancement in
maritime technology, offering the potential for increased efficiency, reduced operational …
maritime technology, offering the potential for increased efficiency, reduced operational …
Reward sha** in multiagent reinforcement learning for self-organizing systems in assembly tasks
Self-organizing systems feature flexibility and robustness for tasks that may endure changes
over time. Various methods, eg, applying task-field and social-field, have been proposed to …
over time. Various methods, eg, applying task-field and social-field, have been proposed to …