partial reinforcement optimizer (PRO). Matlab Source Code
Version 1.0.0 (3,7 Mo) par
Ahmad Taheri
This source code is an implementation of the PRO algorithm to solve CEC2017 benchmark functions.
Partial Reinforcement Optimizer (PRO), is a novel evolutionary optimization algorithm. The major idea behind the PRO comes from a psychological theory in evolutionary learning and training called the partial reinforcement effect (PRE) theory. According to the PRE theory, a learner is intermittently reinforced to learn or strengthen a specific behavior during the learning and training process. The reinforcement patterns significantly impact the response rate and strength of the learner during a reinforcement schedule, achieved by appropriately selecting a reinforcement behavior and the time of applying reinforcement process. In the PRO algorithm, the PRE theory is mathematically modeled to an evolutionary optimization algorithm for solving global optimization problems.
Citation pour cette source
Taheri, Ahmad, et al. “Partial Reinforcement Optimizer: An Evolutionary Optimization Algorithm.” Expert Systems with Applications, Elsevier BV, Oct. 2023, p. 122070, doi:10.1016/j.eswa.2023.122070.
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PRO Matlab Code CEC2017
Version | Publié le | Notes de version | |
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1.0.0 |