Results 71 to 80 of about 35,395 (320)
Continuous-Observation Partially Observable Semi-Markov Decision Processes for Machine Maintenance [PDF]
IEEE Transactions on Reliability, 2017 Partially observable semi-Markov decision processes (POSMDPs) provide a rich framework for planning under both state transition uncertainty and observation uncertainty. In this paper, we widen the literature on POSMDP by studying discrete-state, discrete-action yet continuous-observation POSMDPs.
Zhang, Mimi, Revie, Matthew
openaire +3 more sources
Decentralized Delay Optimal Control for Interference Networks with Limited Renewable Energy Storage
, 2012 In this paper, we consider delay minimization for interference networks with renewable energy source, where the transmission power of a node comes from both the conventional utility power (AC power) and the renewable energy source.
Huang, Huang, Lau, Vincent K. N.
core +1 more source
Mechanism‐Driven Screening of Membrane‐Targeting and Pore‐Forming Antimicrobial Peptides
Advanced Science, EarlyView.To combat antibiotic resistance, this study employs mechanism‐driven screening with machine learning to identify pore‐forming antimicrobial peptides from amphibian and human metaproteomes. Seven peptides are validated, showing minimal toxicity and membrane disruption.
Jiaxuan Li +9 more
wiley +1 more source
Spectrum Access Algoritbm Based on POMDP Model in CVANET
Dianxin kexue, 2014 For the dynamic features of cognitive vehicular Ad Hoc network（CVANET）channel state, a study on spectrum sensing and access of cognitive vehicle users was presented, which was based on framework of partially observable Markov decision process（POMDP ...
Xuefei Zhang, Guoan Zhang, Yancheng Ji
doaj +2 more sources
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes [PDF]
, 2021 Chengchun Shi +3 more
openalex +1 more source
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
On Biologically Inspired Stochastic Reinforcement Deep Learning: A Case Study on Visual Surveillance
IEEE Access, 2019 Here, we present a biologically inspired visual network (BIVnet) for image processing tasks. The proposed model possesses similarities with its neural counterpart and is trained by a stochastic algorithm which employs a partially observable Markov ...
Nadine Hajj, Mariette Awad
doaj +1 more source
A POMDP approach to Affective Dialogue Modeling [PDF]
, 2007 We propose a novel approach to developing a dialogue model that is able to take into account some aspects of the user's affective state and to act appropriately.
Bui, Trung H. +3 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla +4 more
wiley +1 more source
Online Active Perception for Partially Observable Markov Decision Processes with Limited Budget [PDF]
, 2019 Mahsa Ghasemi, Ufuk Topcu
openalex +2 more sources