Technical Seminar Presentation - 2005 Presented By:- Prasanna Kumar Misra(EI200117233) Under the...

Technical Seminar Presentation - 2005

Presented By:- Prasanna Kumar Misra(EI200117233)

Under the guidance of

Ms. Suchilipi Nepak

Presented By

Prasanna Kumar Misra

Roll no-EI200117233

NATIONAL INSTITUTE OF SCIENCE & TECHNOLOGYPalur Hills,Berhampur-761008,Orissa,India

SWARM INTELLIGENCESWARM INTELLIGENCE



WHAT IS SWARM INTELLIGENCEWHAT IS SWARM INTELLIGENCE

•Swarm Intelligence is a property of systems of non-intelligent robots exhibiting collectively intelligent behavior.

•Characteristics of a swarm:

– Distributed, no central control or data source;

– No explicit model of the environment;

– Perception of environment, I.e. sensing;

– Ability to change environment



Swarm systems are examples of behavior-based systems exhibiting:

–Multiple lower level competences;

–Situated in environment;

–Limited time to act;

–Autonomous with no explicit control provided;

–Problem solving is emergent behavior;

–Strong emphasis on reaction and adaptation;

SWARM SYSTEMSSWARM SYSTEMS



MOTIVATIONMOTIVATION

•Robust nature of animal problem-solving

–Simple creatures exhibit complex behavior;

–Behavior modified by dynamic environment.

•Emergent behavior observed in:

–Bacteria

–Ants

–Bees



EMERGENT PROBLEM SOLVINGEMERGENT PROBLEM SOLVING

–Raiding specific areas for food;

–Building and protecting nest;

–Sorting brood and food items;

–Cooperating in carrying large items;

–Emigration of a colony;

–Finding shortest route from nest to food source;

–Preferentially exploiting the richest food source available.



PHEROMONE EVAPORATIONPHEROMONE EVAPORATION



REROUTING OF NETWORK TRAFFICREROUTING OF NETWORK TRAFFIC

•Network structure and dynamics dependent on the function and evolution of biological agents

•Network traffic can be rerouted on the fly with software agents

•Transmission through an alternative (green arrow) node to avoid traffic

•Software agents can perform this rerouting automatically



ANT COLONY & PHEROMONE TRAILSANT COLONY & PHEROMONE TRAILS

• Ants are behaviorally unsophisticated; collectively perform complex tasks.

• Ants have highly developed sophisticated sign-based stigmergy

– communicate using pheromones;

– trails are laid that can be followed by other ants.• Species lay pheromone trails travelling from nest, to nest or possibly in

both directions.

• pheromones evaporate.

• pheromones accumulate with multiple ants using path.



VIRTUAL FORAGINGVIRTUAL FORAGING

• Swarm intelligence investigated foraging behavior of ants.

• Pheromone a chemical substance that attracts other ants.

• Good strategy for finding the shortest path between a nest and a food source

• Optimal routes can be obtained by using artificial ants

• Ant like agents can also cope with dynamic environments



ROBOTICS APPLICATIONROBOTICS APPLICATION

• A machine capable of processing energy.

• Automation capable of processing information.

• Robot capable of processing both energy & information.

• Intelligent swarm is a group of machines capable of forming ordered material patterns unpredictably

• Robots are intentionally programmed very crudely, the similarity between their behavior and that of a swarm of ants is striking.



BANKING APPLICATIONBANKING APPLICATION

• By studying such brood sorting, it was developed that a method for exploring a large database.

• The problem is that many of the customers have never borrowed money from any financial institution.

• If the bank had a way to visualize clusters of people with similar characteristics, loan officers might be able to predict more accurately whether a particular person would repay a loan .

• The artificial ants make their sorting decisions by considering all the different customer characteristics simultaneously.

• The software could mathematically weigh some of the attributes more heavily than others.



SELF ADAPTATIONSELF ADAPTATION

•Shortest paths emerged quickly

•Pheromone and cost sensitivities should vary during search:

–Avoid premature convergence;

–Speed up search considerably.

•Explorers encode sensitivity values:

–Fitness of encoding is cost of route;

–New agents are created with and use genetically-manipulated values for route finding.



PROMISED ADVANTAGESPROMISED ADVANTAGES

• Simple and quasi-identical units• Decentralized control action• Lack of synchronicity• Simple units could be Mass produced, Interchanged,Disposable• Redundancy could result in reliability and adaptation•. Massive computation



CONCLUSION

Swarm Intelligence

•Intelligent set of machines capable of predicting ordered outcome to provide reliability and adaptation describes the intelligence property.

•Manage and design systems that lead to more efficient social organization by understanding the working of networks.

•The agents have the capability of predicting the unpredictable outcomes.

Technical Seminar Presentation - 2005 Presented By:- Prasanna Kumar Misra(EI200117233) Under the...

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