The applicability of reinforcement learning methods in the development of industry 4.0 applications

T Kegyes, Z Süle, J Abonyi - Complexity, 2021 - Wiley Online Library
Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …

[PDF][PDF] Low-cost multipurpose sensor network integrated with iot and webgis for fire safety concerns

ICC Sacramento, V de Oliveira Fernandes… - Acta Scientiarum …, 2023 - researchgate.net
Fire emergencies cause severe damage to Brazilian federal universities. An appropriate and
efficient tool to prevent or detect such events early is multisensory networks from the Internet …

Hidden Markov random field for multi-agent optimal decision in top-coal caving

Y Yang, Z Lin, B Li, X Li, L Cui, K Wang - IEEE Access, 2020 - ieeexplore.ieee.org
Applying model-based learning for the optimal decision of the multi-agent system is not
trivial due to the expensive price or even the impossibility of obtaining the ground truth for …

Analysis daily newspaper distribution in Solo by Agent Based Simulation

IF Febriandini, W Sutopo, M Hisjam - IOP Conference Series …, 2019 - iopscience.iop.org
Agent based simulation is a simulation model that can be used to describe the interaction
between the involved agents. The interaction is generated from observations of human …

Prioritizing public bus transport in urban traffic: a low hanging fruit as a policy measure for sustainable mobility?

A Delitz - unipub.uni-graz.at
To make road transportation more sustainable, it is essential to shift the focus from
maximizing capacity and minimizing disruptions for individual traffic towards prioritizing …

[PDF][PDF] Hidden Markov Random Field for Multi-Agent Optimal Decision in Top-Coal Caving

L CUI, K WANG - scholar.archive.org
Applying model-based learning for the optimal decision of the multi-agent system is not
trivial due to the expensive price or even the impossibility of obtaining the ground truth for …