Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Limits to Natural Selection01:38

Limits to Natural Selection

31.2K
Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
31.2K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

105
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
105
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

58.3K
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).
58.3K
Randomized Experiments01:13

Randomized Experiments

6.8K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
6.8K
Frequency-dependent Selection01:21

Frequency-dependent Selection

21.9K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
21.9K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

45
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...
45

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Co-evolutionary dynamics of asymmetric N-player trust game with margin-driven environmental feedback.

Chaos (Woodbury, N.Y.)·2025
Same author

The impact of feedbacks on evolutionary game dynamics in structured populations.

Chaos (Woodbury, N.Y.)·2025
Same author

Evolutionary dynamics of trust in hierarchical populations with varying investment strategies.

Journal of the Royal Society, Interface·2025
Same author

Impact of community structure on the spread of epidemics on time-varying multiplex networks.

Chaos (Woodbury, N.Y.)·2024
Same author

Analyzing the robustness of LEO satellite networks based on two different attacks and load distribution methods.

Chaos (Woodbury, N.Y.)·2024
Same author

Evolutionary dynamics of N-player sender-receiver game in networks with community structure.

Chaos (Woodbury, N.Y.)·2023

Related Experiment Video

Updated: Jun 14, 2025

Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking
13:40

Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking

Published on: December 16, 2010

16.7K

STP-based control of networked evolutionary games with multi-channel structure.

Zhipeng Zhang1, Xiaotong Jiang1, Chengyi Xia1

  • 1School of Artificial Intelligence, Tiangong University, Tianjin 300387, People's Republic of China.

Chaos (Woodbury, N.Y.)
|September 5, 2024
PubMed
Summary

This study optimizes networked evolutionary games by introducing control delays alongside state delays. New algebraic methods analyze these delays, providing conditions for strategy optimization and controller design in complex systems.

More Related Videos

The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.3K
The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.0K

Related Experiment Videos

Last Updated: Jun 14, 2025

Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking
13:40

Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking

Published on: December 16, 2010

16.7K
The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.3K
The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

2.0K

Area of Science:

  • Game Theory
  • Network Science
  • Control Theory

Background:

  • Channel delay significantly impacts evolutionary game dynamics.
  • Previous work focused on state delays; control delays are newly introduced.
  • Strategy propagation time is a critical factor in real-world games.

Purpose of the Study:

  • To optimize strategy games with both state and control delays.
  • To develop a framework for analyzing evolutionary game dynamics under general information delays.
  • To design feedback controllers for strategy optimization in networked environments.

Main Methods:

  • Utilizing the semi-tensor product of matrices to transform game dynamics into an algebraic form.
  • Analyzing six distinct cases based on control and state delay values.
  • Employing a reachable set method for feedback controller design.

Main Results:

  • Derived sufficient and necessary conditions for strategy optimization existence.
  • Successfully designed feedback controllers based on algebraic equations.
  • Demonstrated the model's feasibility through an illustrative example.

Conclusions:

  • The proposed semi-tensor product method effectively models networked evolutionary games with delays.
  • The findings provide a robust framework for addressing game-based control in complex networks.
  • This research offers valuable insights for understanding and managing evolutionary dynamics in delayed systems.