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<p>Self-Adaptive Learning and Cellular Automata based Mobile Crowdsensing</p>

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Title Statement <p>Self-Adaptive Learning and Cellular Automata based Mobile Crowdsensing</p>
 
Added Entry - Uncontrolled Name Anand, Saurabh ; GLA University, Mathura,Uttar Pradesh, India
Ram, Anant ; GLA University, Mathura,Uttar Pradesh, India
Mishra, Manas Kumar; VIT Bhopal, Bhopal, Madhya Pradesh, India
 
Uncontrolled Index Term Markov decision process, Optimization, Reinforcement learning, Smart crowdsensing
 
Summary, etc. <p>Mobile Crowdsensing (MCS) is frequently utilized for computation assignments, but it is particularly useful for sensing complicated environments. Previously, the MCS platform spent a lot of time and effort establishing incentive mechanisms and task assignment algorithms to encourage mobile users to participate. In actuality, because of their sensing environment and other participants' methodologies, MCS participants face numerous uncertainties, and it is unknown how they interact with one another and make sensing decisions. This study uses the perspectives of MCS participants to develop a web detection arrangement that will maximize their payoffs through MCS participation. Self-adaptive cellular automata-based Markov decision process exhibits interactions among mobile clients and detecting contexts. With the help of Self-Adaptive Support Learning (SASL) and Cellular Automata (CA), we developed a novel method that uses the ideal detecting technique for each client to improve the predicted payoff against random detecting scenarios in a stochastic multi-agent environment. With distinct dynamic sensing, the SASL and CA based smart Crowdsensing enhances user’s payoff, as shown in the simulation.</p>
 
Publication, Distribution, Etc. Journal of Scientific and Industrial Research (JSIR)
2022-03-03 17:23:11
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/JSIR/article/view/53031
 
Data Source Entry Journal of Scientific and Industrial Research (JSIR); ##issue.vol## 81, ##issue.no## 01 (2022): Journal of Scientific and Industrial Research
 
Language Note en
 
Nonspecific Relationship Entry http://op.niscair.res.in/index.php/JSIR/article/download/53031/465591676