Survey on machine learning for traffic-driven service provisioning in optical networks
T Panayiotou, M Michalopoulou… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The unprecedented growth of the global Internet traffic, coupled with the large spatio-
temporal fluctuations that create, to some extent, predictable tidal traffic conditions, are …
temporal fluctuations that create, to some extent, predictable tidal traffic conditions, are …
Human-in-the-loop reinforcement learning: A survey and position on requirements, challenges, and opportunities
Artificial intelligence (AI) and especially reinforcement learning (RL) have the potential to
enable agents to learn and perform tasks autonomously with superhuman performance …
enable agents to learn and perform tasks autonomously with superhuman performance …
Human preference score: Better aligning text-to-image models with human preference
Recent years have witnessed a rapid growth of deep generative models, with text-to-image
models gaining significant attention from the public. However, existing models often …
models gaining significant attention from the public. However, existing models often …
Is rlhf more difficult than standard rl? a theoretical perspective
Abstract Reinforcement learning from Human Feedback (RLHF) learns from preference
signals, while standard Reinforcement Learning (RL) directly learns from reward signals …
signals, while standard Reinforcement Learning (RL) directly learns from reward signals …
Interactive imitation learning in robotics: A survey
Interactive Imitation Learning in Robotics: A Survey Page 1 Interactive Imitation Learning in
Robotics: A Survey Page 2 Other titles in Foundations and Trends® in Robotics A Survey on …
Robotics: A Survey Page 2 Other titles in Foundations and Trends® in Robotics A Survey on …
Wearable EEG electronics for a Brain–AI Closed-Loop System to enhance autonomous machine decision-making
Human nonverbal communication tools are very ambiguous and difficult to transfer to
machines or artificial intelligence (AI). If the AI understands the mental state behind a user's …
machines or artificial intelligence (AI). If the AI understands the mental state behind a user's …
A survey on interactive reinforcement learning: Design principles and open challenges
C Arzate Cruz, T Igarashi - Proceedings of the 2020 ACM designing …, 2020 - dl.acm.org
Interactive reinforcement learning (RL) has been successfully used in various applications in
different fields, which has also motivated HCI researchers to contribute in this area. In this …
different fields, which has also motivated HCI researchers to contribute in this area. In this …
Human-in-the-loop reinforcement learning in continuous-action space
Human-in-the-loop for reinforcement learning (RL) is usually employed to overcome the
challenge of sample inefficiency, in which the human expert provides advice for the agent …
challenge of sample inefficiency, in which the human expert provides advice for the agent …
Towards automated urban planning: When generative and chatgpt-like ai meets urban planning
The two fields of urban planning and artificial intelligence (AI) arose and developed
separately. However, there is now cross-pollination and increasing interest in both fields to …
separately. However, there is now cross-pollination and increasing interest in both fields to …
A review on interactive reinforcement learning from human social feedback
Reinforcement learning agent learns how to perform a task by interacting with the
environment. The use of reinforcement learning in real-life applications has been limited …
environment. The use of reinforcement learning in real-life applications has been limited …