Calibration of an Adaptive Genetic Algorithm for Modeling Opinion Diffusion.
Kara Layne Johnson1, Nicole Bohme Carnegie1
1Department of Mathematical Sciences, Montana State University, Bozeman, MT 59717, USA.
Algorithms
|June 6, 2022
Summary
This study introduces a genetic algorithm for fitting DeGroot opinion diffusion models. The algorithm is robust to most hyperparameter settings, offering guidance for researchers using this optimization technique.
Area of Science:
- Computational Social Science
- Artificial Intelligence
- Mathematical Modeling
Background:
- Genetic algorithms (GAs) are optimization techniques inspired by natural selection.
- They are effective for problems with local optima, using concepts like chromosomes and genes.
- Hyperparameters control the behavior of GA operators.
Purpose of the Study:
- To develop and validate a genetic algorithm for fitting the DeGroot opinion diffusion model with limited data.
- To investigate the impact of various hyperparameter values on the algorithm's performance.
- To provide practical guidance on hyperparameter selection for researchers.
Main Methods:
- Adapted a GA from mixture experiment design, requiring significant modifications for opinion diffusion modeling.
- Implemented selection, blending, crossover, mutation, and survival operators.
- Conducted a simulation study to systematically evaluate hyperparameter sensitivity.
Main Results:
- The developed GA successfully fits the DeGroot opinion diffusion model.
- The algorithm demonstrates robustness across a wide range of hyperparameter values.
- Specific recommendations for initial and adaptive hyperparameter settings are provided.
Conclusions:
- The proposed genetic algorithm is a viable and accessible tool for opinion diffusion modeling.
- Most hyperparameters do not critically affect performance, simplifying initial implementation.
- The study offers valuable insights for optimizing GA performance in social science modeling.
Related Concept Videos
03:33Genetic Drift
40.9K
Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.
40.9K
01:09Mutation, Gene Flow, and Genetic Drift
59.5K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
59.5K
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
107
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
107
01:20Calibration Curves: Linear Least Squares
2.4K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
For data that follow a straight line, the standard method for fitting is the linear...
2.4K
02:39Gene Flow
35.7K
Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.
35.7K
01:24One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
742
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
742