Swarm Intelligence: Overview Flashcards
What is Swarm Intelligence?
Swarm Intelligence (SI) is a branch of artificial intelligence inspired by collective behavior in decentralized, self-organized systems.
What are the fundamental elements of Swarm Intelligence?
Decentralization, Self-Organization, Simple Agents with Local Rules, Positive Feedback, Negative Feedback, Stigmergy, Exploration vs Exploitation.
What is decentralization in Swarm Intelligence?
It refers to the lack of a single controlling entity in the system; agents act independently, and behaviors emerge from local interactions.
How do decentralized systems in SI scale?
They scale easily, as the system can expand with more agents without losing functionality or coordination.
What is self-organization in Swarm Intelligence?
Self-organization means the system organizes itself without external control, with complex behaviors emerging from simple interactions.
What is emergent behavior?
It refers to complex global patterns that arise from simple local interactions between agents in a system.
What are simple agents in Swarm Intelligence?
Simple agents follow local rules based on limited information, and their collective behavior leads to intelligent system-wide actions.
What is positive feedback in Swarm Intelligence?
Positive feedback amplifies successful behaviors within the swarm, leading to reinforcement of certain actions.
Give an example of positive feedback in nature.
Ants laying pheromone trails to food sources, which encourages more ants to follow the same path.
What is negative feedback in Swarm Intelligence?
Negative feedback mechanisms counteract positive feedback to prevent the system from becoming biased towards one solution.
Give an example of negative feedback in nature.
Pheromone trails evaporating over time to prevent ants from following outdated paths.
What is stigmergy?
Stigmergy is a form of indirect communication where agents modify the environment to influence the actions of other agents.
Give an example of stigmergy in nature.
Ants leaving pheromones in their environment to guide other ants toward food.
What is exploration in Swarm Intelligence?
Exploration is when agents search new areas or try new strategies to find better solutions.
What is exploitation in Swarm Intelligence?
Exploitation is when agents use known, successful strategies or solutions to optimize performance.
What is the balance between exploration and exploitation?
Swarm systems must balance exploring new possibilities and exploiting known solutions for optimal performance.
What is Ant Colony Optimization (ACO)?
ACO is an algorithm inspired by ant foraging behavior, used to solve optimization problems like finding the shortest path.
Who developed Ant Colony Optimization (ACO)?
Marco Dorigo in the early 1990s.
What is Particle Swarm Optimization (PSO)?
PSO is an algorithm inspired by social behavior in birds and fish schools, used for optimization problems.
Who developed Particle Swarm Optimization (PSO)?
Kennedy and Eberhart in 1995.
What is the Boids model?
The Boids model, developed by Craig Reynolds, simulates flocking behavior in birds and is a foundational model for swarm behavior.
What are the applications of swarm robotics?
Swarm robotics is used in mapping, search and rescue, environmental monitoring, and decentralized coordination in robotics.
What is hybrid Swarm Intelligence?
Hybrid SI integrates machine learning with swarm systems to enable dynamic adaptation in uncertain environments.
How is Swarm Intelligence used in financial markets?
SI models can analyze collective behaviors in financial markets to predict trends.
How can Swarm Intelligence impact smart cities?
SI can optimize traffic flow, energy distribution, and resource management in smart cities through decentralized control.
What are potential applications of Swarm Intelligence in medicine?
SI-based microrobots or nanobots can navigate the human body for targeted drug delivery or non-invasive surgeries.
What is Quantum Swarm Intelligence?
Quantum SI integrates quantum computing to solve complex optimization problems, potentially enhancing the performance of swarm algorithms.
What ethical considerations are there in Swarm Intelligence?
Ensuring SI systems behave ethically and securely, especially in autonomous military applications, is a key concern.
