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Practical Artificial Intelligence Machine Learning, Bots, and Agent Solutions Using C#

:	Arnaldo Pérez Castaño
:	Practical Artificial Intelligence Machine Learning, Bots, and Agent Solutions Using C#
:	Apress
:	9781484233573
:	1
:	CHF 81.40
:

:	Informatik
:	English

:	701
:	Wasserzeichen/DRM
:	PC/MAC/eReader/Tablet
:	PDF

Discover how all levels Artificial Intelligence (AI) can be present in the most unimaginable scenarios of ordinary lives. This book explores subjects such as neural networks, agents, multi agent systems, supervised learning, and unsupervised learning. These and other topics will be addressed with real world examples, so you can learn fundamental concepts with AI solutions and apply them to your own projects.

People tend to talk about AI as something mystical and unrelated to their ordinary life. Practical Artificial Intelligence provide simple explanations and hands on instructions. Rather than focusing on theory and overly scientific language, this book will enable practitioners of all levels to not only learn about AI but implement its practical uses.

What You'll Learn

Underst nd agents and multi agents and how they are incorporated
How machine learning relates to real world problems and what it means to you
Apply supervised and unsupervised learning techniques and methods in the real world
Implement reinforcement learning, game programming, simulation, and neural networks

< iv>Who This Book Is For

/b>

Computer science students, professionals, and hobbyists interested in AI and its applications.

Arnaldo Pérez Castaño is a computer scientist based in Cuba. He's the author of PrestaShop Recipes (Apress, 2017) and a series of programming books-JavaScript Fácil, HTML y CSS Fácil, and Python Fácil (Marcombo S.A.)-and writes AI related articles for MSDN Magazine, VisualStudioMagazine.com, and Smashing Magazine. He is one of the co-founders of Havana Digital Enterprises and the creator of their first websites, http://www.havanaclassiccarto r.com and www.havanadanceclass.com. His expertise includes Visual Basic, C#, .NET Framework and Artificial Intelligence. Arnaldo offers his services through freelancer.com and served as reviewer forthe Journal of Mathematical Modelling and Algorithms in Operations Research. Cinema and music are some of his passions.

	Table of Contents	5
	About the Author	12
	About the Technical Reviewer	13
	Acknowledgments	14
	Introduction	15
	Chapter 1: Logic	15
	18	15
	What Is Logic?	19
	Propositional Logic	20
	Logical Connectives	23
	Negation	24
	Conjunction	25
	Disjunction	26
	Implication	27
	Equivalence	28
	Laws of Propositional Logic	29
	Normal Forms	33
	Logic Circuits	34
	Practical Problem: Using Inheritance and C# Operators to Evaluate Logic Formulas	38
	Practical Problem: Representing Logic Formulas as Binary Decision Trees	43
	Practical Problem: Transforming a Formula into Negation Normal Form (NNF)	48
	Practical Problem: Transforming a Formula into Conjunctive Normal Form (CNF)	53
	Summary	57
	Chapter 2: Automated Theorem Proving	57
	58	57
	Automated Theorem Proving	59
	Practical Problem: Clauses and CNFs Classes in C#	62
	DPLL Algorithm	72
	Practical Problem: Modeling the Pigeonhole Principle in Propositional Logic	84
	Practical Problem: Finding Whether a Propositional Logic Formula is SAT	85
	First-Order Logic	92
	Predicates in C#	97
	Practical Problem: Cleaning Robot	99
	Summary	106
	Chapter 3: Agents	107
	What’s an Agent?	108
	Agent Properties	111
	Types of Environments	115
	Agents with State	118
	Practical Problem: Modeling the Cleaning Robot as an Agent and Adding State to It	119
	Agent Architectures	129
	Reactive Architectures: Subsumption Architecture	130
	Deliberative Architectures: BDI Architecture	135
	Hybrid Architectures	143
	Touring Machines	147
	InteRRaP	149
	Summary	151
	Chapter 4: Mars Rover	152
	What’s a Mars Rover?	153
	Mars Rover Architecture	155
	Mars Rover Code	158
	Mars Rover Visual Application	191
	Summary	207
	Chapter 5: Multi-Agent Systems	208
	What’s a Multi-Agent System?	209
	Multi-Agent Organization	212
	Communication	214
	Speech Act Theory	216
	Agent Communication Languages (ACL)	219
	Coordination	219
	226	219
	Negotiation Using Contract Net	230
	Social Norms	230
	233	230
	Summary	235
	Chapter 6: Communication in a Multi-Agent System Using WCF	236
	Services	237
	Contracts	239
	Bindings	242
	Endpoints	244
	Publisher/Subscriber Pattern	245
	Practical Problem: Communicating Among Multiple Agents Using WCF	246
	Summary	263
	Chapter 7: Cleaning Agents: A Multi-Agent System Problem	264
	Program Structure	265
	Cleaning Task	266
	Cleaning Agent Platform	269
	Contract Net	271
	FIPA-ACL	277
	MAS Cleaning Agent	282
	GUI	295
	Running the Application	298
	Summary	303
	Chapter 8: Simulation	304
	What Is Simulation?	305
	Discrete-Event Simulation	307
	Probabilistic Distributions	309
	Practical Problem: Airport Simulation	312
	Summary	328
	Chapter 9: Support Vector Machines	329
	What Is a Support Vector Machine (SVM)?	332
	Practical Problem: Linear SVM in C#	342
	Imperfect Separation	357
	Non-linearly Separable Case: Kernel Trick	359
	Sequential Minimal Optimization Algorithm (SMO)	362
	Practical Problem: SMO Implementation	370
	Summary	379
	Chapter 10: Decision Trees	380
	What Is a Decision Tree?	381
	Generating a Decision Tree: ID3 Algorithm	385
	Entropy and Information Gain	388
	Practical Problem: Implementing the ID3 Algorithm	390
	C4.5 Algorithm	406
	Practical Problem: Implementing the C4.5 Algorithm	412
	Summary	423
	Chapter 11: Neural Networks	424
	What Is a Neural Network?	425
	Perceptron: Singular NN	428
	Practical Problem