Principles Of Quantum Artificial Intelligence: Quantum Problem Solving And Machine Learning (Second Edition)

by Andreas Miroslaus Wichert

Overview

This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds.

Product Details

ISBN-13:	9789811224300
Publisher:	World Scientific Publishing Company, Incorporated
Publication date:	08/04/2020
Pages:	496
Product dimensions:	6.00(w) x 9.00(h) x 1.06(d)

Table of Contents

Computation; Problem Solving; Information; Reversible Algorithms; Probability; Bayesian Networks; Introduction to Quantum Physics; Computation with Qubits; Order Finding; Shor's Algorithm; Grover's Algorithm; Quantum Tree Search; Quantum Problem Solving; Input Problem; Statistical Machine Learning; Linear-Algebra Based Quantum Machine Learning; HHL Algorithm; Stochastic Methods; Simulated Annealing; Deep Belief Nets; Adiabatic Quantum Computation; Quantum Annealing; D-Wave's Hamiltonian; Application of Quantum Annealing to Machine Learning; Quantum Cognition; Quantum-like Bayesian Networks; Quantum like-Evolution; Quantum Computation and the Multiverse