Description
INTRODUCTION
Swarm intelligence (SI) is the collective behaviour of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems.
SI systems are typically made up of a population of simple agents or boids interacting locally with one another and with their environment. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local, and to a certain degree random, interactions between such agents lead to the emergence of “intelligent” global behavior, unknown to the individual agents. Natural examples of SI include ant colonies, bird flocking, animal herding, bacterial growth, and fish schooling.
Swarm Intelligence (SI) Seminar Report
Page Length : 17
Content :
- Abstract
- Example Algorithms
- Ant Colony Optimization
- River Formation Dynamics
- Particle Swarm Optimization
- Stochastic Diffusion Search
- Gravitational Search Algorithm
- Intelligent Water Drops
- Charged System Search
- Applications
- Crowd Simulation
- Ant-Based Routing
- References In Popular Culture
- Notable Researchers
Swarm Intelligence (SI) Presentation Report (PPT)
Page Length : 17
Content :
- Background
- What is a Swarm Intelligence (SI)?
- Examples from nature
- Origins and Inspirations of SI
- Ant Colony Optimization
- Particle Swarm Optimization
- Summary
- Why do people use SI?
- Advantages of SI
- Recent developments in SI
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