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The applicability of reinforcement learning methods in the development of industry 4.0 applications
Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …
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 …
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 …
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
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 …
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 …
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 …
trivial due to the expensive price or even the impossibility of obtaining the ground truth for …