Results 131 to 140 of about 5,619,500 (318)

Robustness evaluation of offline reinforcement learning for robot control against action perturbations

International Journal of Advanced Robotic Systems
Offline reinforcement learning, which learns solely from datasets without environmental interaction, has gained attention. This approach, similar to traditional online deep reinforcement learning, is particularly promising for robot control applications.
Shingo Ayabe, Takuto Otomo, Hiroshi Kera, Kazuhiko Kawamoto   +3 more
doaj   +1 more source

Z-Score Experience Replay in Off-Policy Deep Reinforcement Learning

Sensors
Reinforcement learning, as a machine learning method that does not require pre-training data, seeks the optimal policy through the continuous interaction between an agent and its environment.
Yana Yang, Meng Xi, Huiao Dai, Jiabao Wen, Jiachen Yang   +4 more
doaj   +1 more source

Verbal learning and reinforcement: A reexamination of the Premack hypothesis [PDF]

, 1974
Robert W. Schaeffer, Robert J. Nolan
openalex   +1 more source

Momentum in Reinforcement Learning

, 2019
We adapt the optimization's concept of momentum to reinforcement learning. Seeing the state-action value functions as an analog to the gradients in optimization, we interpret momentum as an average of consecutive $q$-functions. We derive Momentum Value Iteration (MoVI), a variation of Value Iteration that incorporates this momentum idea.
Vieillard, Nino, Scherrer, Bruno, Pietquin, Olivier, Geist, Matthieu   +3 more
openaire   +3 more sources

Design and Applications of Multi‐Frequency Programmable Metamaterials for Adaptive Stealth

Advanced Functional Materials, EarlyView.
This article provides a comprehensive overview of metamaterials, including their fundamental principles, properties, synthesis techniques, and applications in stealth, as well as their challenges and future prospects. It covers topics that are more advanced than those typically discussed in existing review articles, while still being closely connected ...
Jonathan Tersur Orasugh, Ankita Mohanty, Amit Malakar, Suryasarathi Bose, Suprakas Sinha Ray   +4 more
wiley   +1 more source

Fixed ratio schedule of reinforcement as a determinant of successive discrimination reversal learning in the pigeon [PDF]

, 1971
Ben A. Williams
openalex   +1 more source

Hierarchical Reinforcement Learning [PDF]

, 1993
A response generating system can be seen as a mapping from a set of external states (inputs) to a set of actions (outputs). This mapping can be done in principally different ways. One method is to divide the state space into a set of discrete states and store the optimal response for each state. This is denominated a memory mapping system.
openaire   +3 more sources

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

An Adaptive Energy Management Strategy for Off-Road Hybrid Tracked Vehicles

Energies
Conventional energy management strategies based on reinforcement learning often fail to achieve their intended performance when applied to driving conditions that significantly deviate from their training conditions.
Lijin Han, Wenhui Shi, Ningkang Yang
doaj   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source