Results 151 to 160 of about 198,528 (317)

Experiential Reinforcement Learning

CoRR
Reinforcement learning has become the central approach for language models (LMs) to learn from environmental reward or feedback. In practice, the environmental feedback is usually sparse and delayed. Learning from such signals is challenging, as LMs must implicitly infer how observed failures should translate into behavioral changes for future ...
Taiwei Shi, Sihao Chen, Bowen Jiang, Linxin Song, Longqi Yang 0001, Jieyu Zhao 0001   +5 more
openaire   +2 more sources

Machine Learning for Adaptive Computer Game Opponents

, 2009
This thesis investigates the use of machine learning techniques in computer games to create a computer player that adapts to its opponent's game-play.
Miles, Jonathan David
core  

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Enhancing Safe Exploration Through Subgoal Guidance

Technologies
Reinforcement learning is a widely used approach for autonomous navigation, but it often struggles to reach distant, long-horizon goals under safety constraints. The primary reason for this suboptimal performance is that safety requirements significantly
Gregory Gorbov, Aleksandr Panov
doaj   +1 more source

Inverse Design of Amorphous Materials With Targeted Properties

Advanced Materials, EarlyView.
AMDEN is a diffusion model framework for the inverse design of amorphous materials with targeted properties. By incorporating Hamiltonian Monte Carlo refinement into the denoising process, the framework overcomes the challenge of generating thermally relaxed disordered structures.
Jonas A. Finkler, Yan Lin, Tao Du, Jilin Hu, Morten M. Smedskjaer   +4 more
wiley   +1 more source

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

Evaluating reinforcement learning for game theory application learning to price airline seats under competition

, 2009
Applied Game Theory has been criticised for not being able to model real decision making situations. A game's sensitive nature and the difficultly in determining the utility payoff functions make it hard for a decision maker to rely upon any game ...
Collins, Andrew
core  

Representation Discovery for Kernel-Based Reinforcement Learning [PDF]

, 2015
Recent years have seen increased interest in non-parametric reinforcement learning. There are now practical kernel-based algorithms for approximating value functions; however, kernel regression requires that the underlying function being approximated be ...
Zewdie, Dawit H., Konidaris, George
core  

Thermodynamic Limits to Molecular Doping in Conjugated Polymers: A Perspective on Phase Behavior and Miscibility

Advanced Materials, EarlyView.
Molecular doping of conjugated polymers is fundamentally constrained by thermodynamic phase behavior. This Perspective reframes doping efficiency and stability in terms of miscibility limits, binodals, and solvus boundaries, highlighting the role of effective interaction parameters and charge transfer.
Somayeh Kashani, Justin Neu, Sung‐Joo Kwon, Runqio Song, Zixuan Chen, Tajah Trapier, Paschalis Gkoupidenis, David Ginger, Wei You, Jasper J. Michels, Harald Ade   +10 more
wiley   +1 more source

Adaptive representations for reinforcement learning [PDF]

, 2007
textIn reinforcement learning, an autonomous agent seeks an effective control policy for tackling a sequential decision task. Unlike in supervised learning, the agent never sees examples of correct or incorrect behavior but receives only a reward ...
Whiteson, Shimon Azariah
core