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Artificial Intelligence for Big Data

You're reading from  Artificial Intelligence for Big Data

Product type Book
Published in May 2018
Publisher Packt
ISBN-13 9781788472173
Pages 384 pages
Edition 1st Edition
Languages
Authors (2):
Anand Deshpande Anand Deshpande
Profile icon Anand Deshpande
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details
Toc

Table of Contents (19) Chapters close

Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
1. Big Data and Artificial Intelligence Systems 2. Ontology for Big Data 3. Learning from Big Data 4. Neural Network for Big Data 5. Deep Big Data Analytics 6. Natural Language Processing 7. Fuzzy Systems 8. Genetic Programming 9. Swarm Intelligence 10. Reinforcement Learning 11. Cyber Security 12. Cognitive Computing 1. Other Books You May Enjoy Index

Multi-objective optimization


So far in this chapter, we have taken the examples of the problem with one objective (finding a food source for an ant colony). However, in real-world scenarios, often there is more than one objective that needs to be met by the individual agents as well as the swarm. For example, in the case of honey bees they need to look for the food source, gather the food, and find a safe and viable place for the beehive. One objective is fulfilled at the cost of another objective. The agent should be programmed to consider the trade-off in the larger interest of the swarm.

As far as possible, the optimization function for the agent should bring optimum solution for more than one objective, but it is not feasible to mutual exclusivity. In such cases, the agent should be able to operate without a central control and decide the objective weightage based on the environmental context and should favor the objective that will fulfill the swarm's overall objective for an elongated...

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