IEEE transactions on neural networks and learning systems
Oct 5, 2022
This article develops an adaptive observation-based efficient reinforcement learning (RL) approach for systems with uncertain drift dynamics. A novel concurrent learning adaptive extended observer (CL-AEO) is first designed to jointly estimate the sy...
Computational intelligence and neuroscience
Sep 28, 2022
Despite the emergence of various human-robot collaboration frameworks, most are not sufficiently flexible to adapt to users with different habits. In this article, a Multimodal Reinforcement Learning Human-Robot Collaboration (MRLC) framework is prop...
Proceedings of the National Academy of Sciences of the United States of America
Sep 19, 2022
Regardless of how much data artificial intelligence agents have available, agents will inevitably encounter previously unseen situations in real-world deployments. Reacting to novel situations by acquiring new information from other people-socially s...
Computational intelligence and neuroscience
Sep 5, 2022
Advances in deep learning significantly affect reinforcement learning, which results in the emergence of Deep RL (DRL). DRL does not need a data set and has the potential beyond the performance of human experts, resulting in significant developments ...
IEEE transactions on neural networks and learning systems
Aug 31, 2022
Efficient neural architecture search (ENAS) achieves novel efficiency for learning architecture with high-performance via parameter sharing and reinforcement learning (RL). In the phase of architecture search, ENAS employs deep scalable architecture ...
Computational intelligence and neuroscience
Aug 31, 2022
For the problems of unreasonable computation offloading and uneven resource allocation in Mobile Edge Computing (MEC), this paper proposes a task offloading and resource allocation strategy based on deep learning for MEC. Firstly, in the multiuser mu...
Conformer-RL is an open-source Python package for applying deep reinforcement learning (RL) to the task of generating a diverse set of low-energy conformations for a single molecule. The library features a simple interface to train a deep RL conforme...
Journal of chemical information and modeling
Aug 12, 2022
Automatic design of molecules with specific chemical and biochemical properties is an important process in material informatics and computational drug discovery. In this study, we designed a novel coarse-grained tree representation of molecules (Reve...
From the computational point of view, musculoskeletal control is the problem of controlling high degrees of freedom and dynamic multi-body system that is driven by redundant muscle units. A critical challenge in the control perspective of skeletal jo...
IEEE transactions on neural networks and learning systems
Aug 3, 2022
A central capability of a long-lived reinforcement learning (RL) agent is to incrementally adapt its behavior as its environment changes and to incrementally build upon previous experiences to facilitate future learning in real-world scenarios. In th...
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