An information-theoretic perspective on intrinsic motivation in reinforcement learning: A survey

A Aubret, L Matignon, S Hassas - Entropy, 2023 - mdpi.com
The reinforcement learning (RL) research area is very active, with an important number of
new contributions, especially considering the emergent field of deep RL (DRL). However, a …

Prototypical Context-Aware Dynamics for Generalization in Visual Control With Model-Based Reinforcement Learning

J Wang, Q Zhang, Y Mu, D Li, D Zhao… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
The latent world model, which efficiently represents high-dimensional observations within a
latent space, has shown promise in reinforcement learning-based policies for visual control …

Memorability-based multimedia analytics for robotic interestingness prediction system using trimmed Q-learning algorithm

H Ali, SO Gilani, A Waris, UH Shah, MAK Khattak… - Scientific reports, 2023 - nature.com
Mobile robots are increasingly employed in today's environment. Perceiving the
environment to perform a task plays a major role in the robots. The service robots are wisely …

Offline reinforcement learning in high-dimensional stochastic environments

F Hêche, O Barakat, T Desmettre, T Marx… - Neural Computing and …, 2024 - Springer
Offline reinforcement learning (RL) has emerged as a promising paradigm for real-world
applications since it aims to train policies directly from datasets of past interactions with the …

[HTML][HTML] Improving robot dual-system motor learning with intrinsically motivated meta-control and latent-space experience imagination

MB Hafez, C Weber, M Kerzel, S Wermter - Robotics and Autonomous …, 2020 - Elsevier
Combining model-based and model-free learning systems has been shown to improve the
sample efficiency of learning to perform complex robotic tasks. However, dual-system …

Airline dynamic pricing with patient customers using deep exploration-based reinforcement learning

S Jo, GM Lee, I Moon - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
This paper addresses a crucial issue in the airline industry by tackling a dynamic pricing
problem in the presence of patient customers, a scenario that has gained significance due to …

Latent Landmark Graph for Efficient Exploration-exploitation Balance in Hierarchical Reinforcement Learning

Q Zhang, H Zhang, D ** artificial agents with sensorimotor skills is to use self-
exploration. To do this efficiently is critical, as time and data collection are costly. In this …