Results 81 to 90 of about 57,303 (303)

Comparing Labelled Markov Decision Processes

CoRR, 2020
35 pages, 7 ...
Stefan Kiefer, Qiyi Tang 0001
openaire   +4 more sources

Ultra‐Wide‐Field Noninvasive Imaging Through Scattering Media Via Physics‐Guided Deep Learning

Advanced Science, EarlyView.
We propose a physics‐guided adaptive dual‐domain learning method for ultra‐wide‐field noninvasive imaging through scattering media, namely UNI‐Net. Our method not only reduces the requirement for real experimental data by an order of magnitude but also enables clear imaging of complex scenes with an ultra‐large field of view, which is 164 times the OME
Lintao Peng, Mingwei He, Jeff Zhu, Sujit K. Sahoo, Liheng Bian, Cuong Dang   +5 more
wiley   +1 more source

Communicating via Markov Decision Processes

, 2021
ICML ...
Sokota, S, de Witt, CS, Igl, M, Zintgraf, L, Torr, P, Strohmeier, M, Kolter, JZ, Whiteson, S, Foerster, J   +8 more
openaire   +4 more sources

A stopping rule for discounted Markov decision processes with finite action sets [PDF]

, 2009
summary:In a Discounted Markov Decision Process (DMDP) with finite action sets the Value Iteration Algorithm, under suitable conditions, leads to an optimal policy in a finite number of steps.
Lemus-Rodríguez, Enrique, Cruz-Suárez, Daniel, Montes-de-Oca, Raúl   +2 more
core  

Diffusion‐Based Generative Model With Scaffold‐Hopping Strategy Yields Highly Potent Bioactive Molecules

Advanced Science, EarlyView.
SMarT‐Diff introduces a multi‐objective generative paradigm that integrates scaffold hopping with structure‐aware scoring to enable controlled exploration beyond the training distribution. The framework consistently balances drug‐likeness, synthesizes accessibility and bioactivity, yielding chemically diverse candidates with enhanced properties.
Yuwei Yang, Xiaoqing Gong, Shukai Gu, Jing Li, Bo Liu, Yanan Tian, Qianqian Zhang, Xiaojun Yao, Huanxiang Liu   +8 more
wiley   +1 more source

Underwater chemical plume tracing based on partially observable Markov decision process

International Journal of Advanced Robotic Systems, 2019
Chemical plume tracing based on autonomous underwater vehicle uses chemical as a guidance to navigate and search in the unknown environments. To solve the key issue of tracing and locating the source, this article proposes a path-planning strategy based ...
Jiu Hai-Feng, Chen Yu, Deng Wei, Pang Shuo   +3 more
doaj   +1 more source

PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes

Advanced Science, EarlyView.
A plant genomic foundation model pre‐trained on 12 species enables both accurate gene prediction and de novo gene design. Through AI‐human knowledge screening, seven designed sequences showed transcriptional activity in plants, with two expressing stable proteins—demonstrating the first DNA‐RNA‐protein expression of LLM‐generated genes in plants and ...
Changhao Li, Qizhe Zhang, Hanchen Chen, Kepeng Lin, Chengfang Luo, Mengying Yang, Wei Xu, Fan Yao, Jianbing Yan, Qing‐Yong Yang, Xuehai Hu   +10 more
wiley   +1 more source

Monitored Markov Decision Processes

International Joint Conference on Autonomous Agents and Multiagent Systems
In reinforcement learning (RL), an agent learns to perform a task by interacting with an environment and receiving feedback (a numerical reward) for its actions. However, the assumption that rewards are always observable is often not applicable in real-world problems. For example, the agent may need to ask a human to supervise its actions or activate a
Simone Parisi, Montaser Mohammedalamen, Alireza Kazemipour, Matthew E. Taylor, Michael Bowling   +4 more
openaire   +3 more sources

Modelling the profitability of credit cards by Markov decision processes

, 2009
This paper derives a model for the profitability of credit cards, which allow lenders to find the optimal dynamic credit limit policy. The model is a Markov decision process, where the states of the system are based on the borrower's behavioural score ...
Thomas, Lyn C., So, Mee Chi
core  

Full‐Stack Architectures for Intelligent Brain‐Computer Interfaces

Advanced Science, EarlyView.
System‐level overview of brain–computer interfaces (BCIs), illustrating the integration of neural signal acquisition, wireless transmission, and adaptive decoding. Advanced electrode, tissue interfaces, energy‐efficient communication, and robust algorithms collectively enable stable signal quality, real‐time processing, and closed‐loop operation ...
Hee Kyu Lee, Hyun Bin Kim, Sang Uk Park, Janghoon Joo, Jinhong Min, Geumbee Lee, Joohoon Kang, Hyoyoung Jeong, Jae‐Young Yoo, Sang Min Won   +9 more
wiley   +1 more source