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

Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

4.3K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
4.3K
Robbers Cave04:49

Robbers Cave

14.3K
During the 1950s, the landmark Robbers Cave experiment demonstrated that when groups must compete with one another, intergroup conflict, hostility, and even violence may result. At the Oklahoman summer camp, two troops of boys—termed the Rattlers and the Eagles—took part in a week-long tournament. During this time, their negativity culminated in derogatory name-calling, fistfights, and even vandalism and destruction of property. However, this work also revealed that such tension...
14.3K
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

5.5K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
5.5K
Predator-Prey Interactions02:39

Predator-Prey Interactions

16.6K
Predators consume prey for energy. Predators that acquire prey and prey that avoid predation both increase their chances of survival and reproduction (i.e., fitness). Routine predator-prey interactions elicit mutual adaptations that improve predator offenses, such as claws, teeth, and speed, as well as prey defenses, including crypsis, aposematism, and mimicry. Thus, predator-prey interactions resemble an evolutionary arms race.
16.6K
Types of Collisions - II01:19

Types of Collisions - II

8.0K
When two or more objects collide with each other, they can stick together to form one single composite object (after collision). The total mass of the object after the collision is the sum of the masses of the original objects, and it moves with a velocity dictated by the conservation of momentum. Although the system's total momentum remains constant, the kinetic energy decreases, and thus such a collision is an inelastic collision. Most of the collisions between objects in daily life are...
8.0K
Dynamic Equilibrium02:20

Dynamic Equilibrium

52.2K
A reversible chemical reaction represents a chemical process that proceeds in both forward (left to right) and reverse (right to left) directions. When the rates of the forward and reverse reactions are equal, the concentrations of the reactant and product species remain constant over time and the system is at equilibrium. A special double arrow is used to emphasize the reversible nature of the reaction. The relative concentrations of reactants and products in equilibrium systems vary greatly;...
52.2K

You might also read

Related Articles

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

Sort by
Same author

Introduction to focus issue: Intelligent game on networked systems: Optimization, evolution and control.

Chaos (Woodbury, N.Y.)·2026
Same author

A combat game model between hierarchical networks.

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

Replicator dynamics with feedback-evolving games in heterogeneous populations.

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

Promotion of cooperation in a structured population with environmental feedbacks.

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

Publisher's Note: "A combat game model with inter-network confrontation and intra-network cooperation" [Chaos 33, 033123 (2023)].

Chaos (Woodbury, N.Y.)·2023
Same author

The Strength of Structural Diversity in Online Social Networks.

Research (Washington, D.C.)·2021

Related Experiment Video

Updated: Aug 4, 2025

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

9.4K

A combat game model with inter-network confrontation and intra-network cooperation.

Hao Chen1, Lin Wang1, Xiaofan Wang1

  • 1Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, People's Republic of China.

Chaos (Woodbury, N.Y.)
|April 1, 2023
PubMed
Summary

Network structure significantly impacts combat outcomes. Grid networks excel, while random networks falter. Cooperation strategies vary in effectiveness based on network type and depth.

More Related Videos

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

2.1K
Peering into the Dynamics of Social Interactions: Measuring Play Fighting in Rats
15:01

Peering into the Dynamics of Social Interactions: Measuring Play Fighting in Rats

Published on: January 18, 2013

15.4K

Related Experiment Videos

Last Updated: Aug 4, 2025

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

9.4K
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

2.1K
Peering into the Dynamics of Social Interactions: Measuring Play Fighting in Rats
15:01

Peering into the Dynamics of Social Interactions: Measuring Play Fighting in Rats

Published on: January 18, 2013

15.4K

Area of Science:

  • Evolutionary game theory
  • Network science
  • Computational social science

Background:

  • Inter-network conflict and intra-network cooperation are key in evolutionary history.
  • Limited research exists on combat mechanisms between structured systems and cooperation's role.

Purpose of the Study:

  • To propose and analyze a two-network combat game model.
  • To investigate the influence of network structure and cooperation on combat success.

Main Methods:

  • Simulated combat between four network structures: Erdős-Rényi (ER) random, grid, small-world, and scale-free networks.
  • Analyzed combat outcomes based on network properties, cooperation breadth, and depth.

Main Results:

  • Grid networks achieved the highest win rates; ER random networks had the lowest.
  • Small-world properties and heterogeneity enhanced combat success.
  • Broader cooperation aided winning on grid and scale-free networks but hindered on ER and Watts-Strogatz (WS) networks. Deeper cooperation generally benefited winning, except on scale-free networks.

Conclusions:

  • Network structure and cooperation strategies critically influence adversarial interactions.
  • Findings offer insights into the dynamics of structured systems in conflict and cooperation scenarios.