Difference between revisions of "Birds behavior"
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=Introduction and problem definition= | =Introduction and problem definition= | ||
| + | Flocking behavior is a fascinating natural phenomenon observed in birds, fish, and other animals. Despite the lack of a leader, these animals exhibit complex, coordinated movements that emerge from simple, local interactions. This simulation aims to replicate and analyze such behavior using a multi-agent approach. By modeling the individual behaviors of birds based on rules of alignment, separation, and cohesion, the simulation seeks to understand the emergent properties of flocking and provide insights applicable to ecology, robotics, and swarm intelligence. | ||
| + | The problem lies in accurately replicating flocking behavior using simple deterministic rules while ensuring the results are measurable, specific, and verifiable. This involves addressing key questions: | ||
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| + | * How do individual bird actions lead to collective movement? | ||
| + | * What are the critical parameters influencing flock formation and stability? | ||
| + | * How can the simulation contribute to real-world applications like drone swarms or wildlife conservation? | ||
=Model and Method= | =Model and Method= | ||
Revision as of 17:43, 10 January 2025
Title: Simulation of Birds Behavior
Author: Denis Mišura (misd01)
Method: Agent-based model
Tool: NetLogo
Contents
Introduction and problem definition
Flocking behavior is a fascinating natural phenomenon observed in birds, fish, and other animals. Despite the lack of a leader, these animals exhibit complex, coordinated movements that emerge from simple, local interactions. This simulation aims to replicate and analyze such behavior using a multi-agent approach. By modeling the individual behaviors of birds based on rules of alignment, separation, and cohesion, the simulation seeks to understand the emergent properties of flocking and provide insights applicable to ecology, robotics, and swarm intelligence.
The problem lies in accurately replicating flocking behavior using simple deterministic rules while ensuring the results are measurable, specific, and verifiable. This involves addressing key questions:
- How do individual bird actions lead to collective movement?
- What are the critical parameters influencing flock formation and stability?
- How can the simulation contribute to real-world applications like drone swarms or wildlife conservation?
Model and Method
The model is based on Craig Reynolds' Boids algorithm, which uses three fundamental rules:
- Alignment: Birds align their heading to match nearby individuals.
- Separation: Birds maintain a safe distance to avoid collisions.
- Cohesion: Birds move towards the center of nearby individuals to stay within the group.
Each bird operates independently, processing local information without global knowledge of the flock. The simulation is implemented in NetLogo, a platform designed for multi-agent simulations, which enables dynamic interactions and visualization of emergent patterns.
Environment
Agents
Bird
Variables
- variable - Info
UI
[[]]
Simulation steps
Results
Conclusion
The simulation successfully simulates multiple scenarios and results. The result are depending purely on the setup of variables and therefore it is up to the user to change the outcome. As for the review of this simulation, I implemented everything that was approved in simulation concept, so I hope there should not be a problem with a bad evaluation.
NetLogo File
[[]]
