partial reinforcement optimizer (PRO). Matlab Source Code
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.
引用格式
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.
| 版本 | 已发布 | 发行说明 | Action |
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| 1.0.0 |
