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De Gruyter Math Optimization for AI - Heuristic & Metaheuristic Methods

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Description

Master mathematical optimisation techniques essential for artificial intelligence, robotics and machine learning. This comprehensive guide from De Gruyter explores heuristic and metaheuristic methods that solve complex computational problems efficiently. Perfect for researchers, engineers and students seeking to understand the mathematical foundations driving modern AI systems. The second volume in the Mathematical Methods in the Digital Age series builds on core concepts to deliver practical strategies for real-world applications. Whether optimising neural networks, improving robotics algorithms or refining machine learning models, this text provides the theoretical knowledge and methodological frameworks needed to tackle challenging problems in computational intelligence. Ideal for postgraduate study, professional development and academic research.

Key Features

Covers heuristic and metaheuristic optimisation methods specifically designed for artificial intelligence and machine learning applications.

Published by De Gruyter as Volume 2 in the Mathematical Methods in the Digital Age series, ensuring academic rigour and peer-reviewed content.

Explores practical optimisation strategies applicable to robotics, neural network training and algorithmic design.

Provides mathematical foundations and theoretical frameworks for understanding and implementing advanced optimisation techniques.

Suitable for graduate-level study, research applications and professional advancement in AI and computational science fields.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
21 April 2025
Listed Since
09 August 2024

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