Results 21 to 30 of about 6,930,474 (290)

Evolving Constrained Reinforcement Learning Policy

2023 International Joint Conference on Neural Networks (IJCNN), 2023
accepted by the 2023 International Joint Conference on Neural Networks (IJCNN)
Chengpeng Hu, Jiyuan Pei, Jialin Liu 0001, Xin Yao 0001   +3 more
openaire   +4 more sources

Inverse Constrained Reinforcement Learning

CoRR, 2020
Camera-ready version for ICML ...
Usman Anwar, Shehryar Malik, Alireza Aghasi, Ali Ahmed 0004   +3 more
openaire   +4 more sources

Locally Constrained Representations in Reinforcement Learning

CoRR, 2022
The success of Reinforcement Learning (RL) heavily relies on the ability to learn robust representations from the observations of the environment. In most cases, the representations learned purely by the reinforcement learning loss can differ vastly across states depending on how the value functions change. However, the representations learned need not
Nath, Somjit, Arora, Rushiv, Kahou, Samira Ebrahimi   +2 more
openaire   +2 more sources

Safe and Efficient Operation with Constrained Hierarchical Reinforcement Learning

, 2023
Hierarchical Reinforcement Learning (HRL) holds the promise of enhancing sample efficiency and generalization capabilities of Reinforcement Learning (RL) agents by leveraging task decomposition and temporal abstraction, which aligns with human reasoning.
Günnemann, Stephan, Roscher, Karsten, Schmoeller da Roza, Felippe   +2 more
core   +1 more source

An SDN Controller-Based Network Slicing Scheme Using Constrained Reinforcement Learning

IEEE Access, 2022
In order to meet the strong diversification of services that demand network flexibility that will be able to serve the dire need for transmission resources, network slicing was embraced as a plausible solution.
Mduduzi C. Mduduzi Hlophe, Bodhaswar T. Maharaj   +1 more
doaj   +1 more source

Constrained Reinforcement Learning for Dexterous Manipulation

CoRR, 2023
Accepted in the International Workshop on Safe Reinforcement Learning at the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022).
Abhineet Jain, Jack Kolb, Harish Ravichandar   +2 more
openaire   +2 more sources

A Survey of Safe Reinforcement Learning Methods in Robotics [PDF]

ITM Web of Conferences
Reinforcement learning has achieved remarkable results in complex decision-making tasks such as robot control, but its deployment in real-world environments still faces safety challenges.
Xie Yuen
doaj   +1 more source

Research into Autonomous Vehicles Following and Obstacle Avoidance Based on Deep Reinforcement Learning Method under Map Constraints

Sensors, 2023
Compared with traditional rule-based algorithms, deep reinforcement learning methods in autonomous driving are able to reduce the response time of vehicles to the driving environment and fully exploit the advantages of autopilot.
Zheng Li, Shihua Yuan, Xufeng Yin, Xueyuan Li, Shouxing Tang   +4 more
doaj   +1 more source

Reinforcement learning in populations of spiking neurons [PDF]

, 2008
Population coding is widely regarded as a key mechanism for achieving reliable behavioral responses in the face of neuronal variability. But in standard reinforcement learning a flip-side becomes apparent.
Urbanczik, R, Walter Senn, Robert Urbanczik, Senn, W   +3 more
core   +1 more source

Routing algorithms as tools for integrating social distancing with emergency evacuation

Scientific Reports, 2021
One of the lessons from the COVID-19 pandemic is the importance of social distancing, even in challenging circumstances such as pre-hurricane evacuation. To explore the implications of integrating social distancing with evacuation operations, we describe
Yi-Lin Tsai, Chetanya Rastogi, Peter K. Kitanidis, Christopher B. Field   +3 more
doaj   +1 more source