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Practical artificial intelligence : machine learning, bots, and agent solutions using C# /
Discover how all levels Artificial Intelligence (AI) can be present in the most unimaginable scenarios of ordinary lives. This book explores neural networks, agents, multi agent systems, supervised learning, and unsupervised learning. These and other topics will be addressed with real world examples...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
Apress,
[2018]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Intro; Table of Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Logic & AI; What Is Logic?; Propositional Logic; Logical Connectives; Negation; Conjunction; Disjunction; Implication; Equivalence; Laws of Propositional Logic; Normal Forms; Logic Circuits; Practical Problem: Using Inheritance and C# Operators to Evaluate Logic Formulas; Practical Problem: Representing Logic Formulas as Binary Decision Trees; Practical Problem: Transforming a Formula into Negation Normal Form (NNF)
- Practical Problem: Transforming a Formula into Conjunctive Normal Form (CNF); Summary; Chapter 2: Automated Theorem Proving & First-Order Logic; Automated Theorem Proving; Practical Problem: Clauses and CNFs Classes in C#; DPLL Algorithm; Practical Problem: Modeling the Pigeonhole Principle in Propositional Logic; Practical Problem: Finding Whether a Propositional Logic Formula is SAT; First-Order Logic; Predicates in C#; Practical Problem: Cleaning Robot; Summary; Chapter 3: Agents; What's an Agent?; Agent Properties; Types of Environments; Agents with State
- Practical Problem: Modeling the Cleaning Robot as an Agent and Adding State to It; Agent Architectures; Reactive Architectures: Subsumption Architecture; Deliberative Architectures: BDI Architecture; Hybrid Architectures; Touring Machines; InteRRaP; Summary; Chapter 4: Mars Rover; What's a Mars Rover?; Mars Rover Architecture; Mars Rover Code; Mars Rover Visual Application; Summary; Chapter 5: Multi-Agent Systems; What's a Multi-Agent System?; Multi-Agent Organization; Communication; Speech Act Theory; Agent Communication Languages (ACL); Coordination & Cooperation
- Negotiation Using Contract Net; Social Norms & Societies; Summary; Chapter 6: Communication in a Multi-Agent System Using WCF; Services; Contracts; Bindings; Endpoints; Publisher/Subscriber Pattern; Practical Problem: Communicating Among Multiple Agents Using WCF; Summary; Chapter 7: Cleaning Agents: A Multi-Agent System Problem; Program Structure; Cleaning Task; Cleaning Agent Platform; Contract Net; FIPA-ACL; MAS Cleaning Agent; GUI; Running the Application; Summary; Chapter 8: Simulation; What Is Simulation?; Discrete-Event Simulation; Probabilistic Distributions
- Practical Problem: Airport Simulation; Summary; Chapter 9: Support Vector Machines; What Is a Support Vector Machine (SVM)?; Practical Problem: Linear SVM in C#; Imperfect Separation; Non-linearly Separable Case: Kernel Trick; Sequential Minimal Optimization Algorithm (SMO); Practical Problem: SMO Implementation; Summary; Chapter 10: Decision Trees; What Is a Decision Tree?; Generating a Decision Tree: ID3 Algorithm; Entropy and Information Gain; Practical Problem: Implementing the ID3 Algorithm; C4.5 Algorithm; Practical Problem: Implementing the C4.5 Algorithm; Summary