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An information-theoretic perspective on intrinsic motivation in reinforcement learning: A survey
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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 …
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 …
exploration. To do this efficiently is critical, as time and data collection are costly. In this …