Results 71 to 80 of about 5,928 (266)
Average Reward Optimality in Semi-Markov Decision Processes with Costly Interventions
, 2023 In this note we consider semi-Markov reward decision processes evolving on finite state spaces. We focus attention on average reward models, i.e. we establish explicit formulas for the growth rate of the total expected reward. In contrast to the standard
Sladký, Karel
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A Novel Two‐Stage Flexible Flow Shop Batch Scheduling Model for Grinding Workshops
Naval Research Logistics (NRL), EarlyView.ABSTRACT The growing need for data storage in data centers has increased the demand for mechanical hard disks due to their low cost and high reliability. Aluminum substrates are the most popular base plates for mechanical hard disks because of their high hardness and low cost.
Jun Xu +4 more
wiley +1 more source
Bridging Human and Plant Adaptations for Climate Resilience
PLANTS, PEOPLE, PLANET, EarlyView.Climate change is transforming agriculture through both gradual shifts and increasingly unpredictable extremes, challenging farmers' ability to protect crops and livelihoods. This study brings together farmer experiences and plant adaptation strategies to explore how people and plants respond to similar climate pressures.
Nicola Favretto +3 more
wiley +1 more source
, 2019 summary:This paper studies a class of discrete-time discounted semi-Markov control model on Borel spaces. We assume possibly unbounded costs and a non-stationary exponential form in the discount factor which depends of on a rate, called the discount rate.
H. García, Yofre +2 more
core +1 more source
Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma
CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 540-550, March 2025.ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell ...
Kevin Atsou +4 more
wiley +1 more source
Quality and Reliability Engineering International, EarlyView.ABSTRACT A repairable system operates under a maintenance strategy involving scheduled preventive maintenance (PM) and corrective repair actions following failures. This study develops an exact analytical methodology using Markov chains with discrete states and time to calculate the expected number of failures E[N(t)]$\mathop {\mathbb {E}}[N(t)]$ under
Danilo G. O. Valadares +3 more
wiley +1 more source
SEMI-MARKOV DECISION PROCESSES WITH COUNTABLE STATE SPACE AND COMPACT ACTION SPACE
, 1978 We shall be concerned with the optimization problem of semi-Markov decision processes with countable state space and compact action space. Defined is the generalized reward function associated with the semi-Markov decision processes which include the ...
安田, 正實, Yasuda, Masami
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Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models
International Journal of Satellite Communications and Networking, EarlyView.ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel +2 more
wiley +1 more source
A policy gradient method for semi-Markov decision processes
, 2002 Solving a semi-Markov decision process (SMDP) using value or policy iteration requires precise knowledge of the probabilistic model and suffers from the curse of dimensionality.
Sumeetpal S. Singh +2 more
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Network Latency Estimation for Telesurgery Using Deep Reinforcement Learning
SmartBot, EarlyView.Overview of the proposed two‐stage deep reinforcement learning framework for network latency prediction in telesurgery. The pipeline includes data collection from simulated catheter navigation sessions (Philippines–Botswana), feature engineering, DQN‐based direction prediction (85.8% accuracy), direction‐to‐value transformation, and value forecasting ...
Bakang Kgopolo +2 more
wiley +1 more source