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Software Architect's Handbook: Become a successful software architect by implementing effective architecture concepts
Software Architect's Handbook: Become a successful software architect by implementing effective architecture concepts

A comprehensive guide to exploring software architecture concepts and implementing best practices

Key Features

  • Enhance your skills to grow your career as a software architect
  • Design efficient software architectures using patterns and best practices
  • Learn...
The Nature of Code: Simulating Natural Systems with Processing
The Nature of Code: Simulating Natural Systems with Processing
How can we capture the unpredictable evolutionary and emergent properties of nature in software? How can understanding the mathematical principles behind our physical world help us to create digital worlds? This book focuses on a range of programming strategies and techniques behind computer simulations of natural systems, from elementary...
Simulation-Based Algorithms for Markov Decision Processes (Communications and Control Engineering)
Simulation-Based Algorithms for Markov Decision Processes (Communications and Control Engineering)
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.  Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical...
Design by Evolution: Advances in Evolutionary Design (Natural Computing Series)
Design by Evolution: Advances in Evolutionary Design (Natural Computing Series)

Evolution is Nature’s design process. The natural world is full of wonderful examples of its successes, from engineering design feats such as powered flight, to the design of complex optical systems such as the mammalian eye, to the merely stunningly beautiful designs of orchids or birds of paradise. With increasing...

Network-Based Distributed Planning Using Coevolutionary Algorithms (Intelligent Control and Intelligent Automation - Vol. 13)
Network-Based Distributed Planning Using Coevolutionary Algorithms (Intelligent Control and Intelligent Automation - Vol. 13)
In this book, efficient and scalable coevolutionary algorithms for distributed, network-based decision-making, which utilize objective functions are developed in a networked environment where internode communications are a primary factor in system performance.A theoretical foundation for this class of coevolutionary algorithms is introduced...
Electronic Design Automation of Analog ICs combining Gradient Models with Multi-Objective Evolutionary Algorithms (SpringerBriefs in Applied Sciences and Technology)
Electronic Design Automation of Analog ICs combining Gradient Models with Multi-Objective Evolutionary Algorithms (SpringerBriefs in Applied Sciences and Technology)
This book applies to the scientific area of electronic design automation (EDA) and addresses the automatic sizing of analog integrated circuits (ICs). Particularly, this book presents an approach to enhance a state-of-the-art layout-aware circuit-level optimizer (GENOM-POF), by embedding statistical knowledge from an automatically generated...
Introduction to Evolutionary Computing (Natural Computing Series)
Introduction to Evolutionary Computing (Natural Computing Series)

The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to...

Evolutionary Computation 1: Basic Algorithms and Operators
Evolutionary Computation 1: Basic Algorithms and Operators
The original Handbook of Evolutionary Computation (Back et a1 1997) was designed to fulfil1 the need for a broad-based reference book reflecting the important role that evolutionary computation plays in a variety of disciplinesranging from the natural sciences and engineering to evolutionary biology and computer...
Introduction to Evolutionary Algorithms (Decision Engineering)
Introduction to Evolutionary Algorithms (Decision Engineering)
Evolutionary algorithms are becoming increasingly attractive across various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science and economics. Introduction to Evolutionary Algorithms presents an insightful, comprehensive, and up-to-date treatment of evolutionary algorithms....
Data Mining for Systems Biology: Methods and Protocols (Methods in Molecular Biology)
Data Mining for Systems Biology: Methods and Protocols (Methods in Molecular Biology)

The post-genomic revolution is witnessing the generation of petabytes of data annually, with deep implications ranging across evolutionary theory, developmental biology, agriculture, and disease processes. Data Mining for Systems Biology: Methods and Protocols, surveys and demonstrates the science and technology of converting...

Computational Intelligence: An Introduction
Computational Intelligence: An Introduction
Can computers be intelligent?

This question causes even more debate than the definitions of intelligence do.

Computational intelligence is the study of adaptive mechanisms to enable or facilitate intelligent behaviour in complex and changing environments. As such, computational intelligence encompasses artificial neural networks,...

Evolutionary Optimization Algorithms
Evolutionary Optimization Algorithms

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms

Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant...

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