Table of contents for Artificial intelligence : a systems approach / M. Tim Jones.

Bibliographic record and links to related information available from the Library of Congress catalog.

Note: Contents data are machine generated based on pre-publication provided by the publisher. Contents may have variations from the printed book or be incomplete or contain other coding.


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Table of Contents
Chapter 1 Introduction to AI
	Introduction
	What is Intelligence?
	The Search for Mechanical Intelligence
	The Very Early Days (the early 1950's)
		Alan Turing
		AI, Problem Solving and Games
	Artificial Intelligence Emerges as a Field
		The Dartmouth AI Summer Research Project
		Building Tools for AI
		The Focus on Strong AI
		Constrained Applications
		Bottom-Up Approaches Emerge
	AI's Winter
		Results-Oriented Applications
		Additional AI Tools Emerge
		Neat vs. Scruffy Approaches
	AI Remerges
		The Silent Return
		Messy and Scruffy Approaches Take Hold
		Agent Systems
	AI Inter-disciplinary R&D
	Systems Approach
	Overview of this Book
		Uninformed Search
		Informed Search
		AI and Games
		Knowledge Representation
		Machine Learning
		Evolutionary Computation
		Neural Networks Part 1
		Neural Networks Part 2
		Intelligent Agents
		Biologically Inspired and Hybrid Models
		Languages of AI
	Summary
	References
	Resources
	Exercises
Chapter 2 Uninformed Search
Search and AI
Classes of Search
General State Space Search
		Search in a Physical Space
		Search in a Puzzle Space
		Search in an Adversarial Game Space
Trees, Graphs and Representation
Uninformed Search
		Helper APIs
		General Search Paradigms
		Depth-First Search
		Depth-Limited Search
		Iterative Deepening Search
		Breadth-First Search
		Bidirectional Search
		Uniform-Cost Search
Improvements
Algorithm Advantages
Chapter Summary
Algorithms Summary
References
Exercises
Chapter 3 Informed Search
Search and AI
Best-First Search
	Best-First Search and the N-Queens Problem
	Best-First Search Implementation
	Variants of Best-First Search
A* Search
	A* Search and the Eight Puzzle
	Eight Puzzle Representation
	A* Search Implementation
	Eight Puzzle Demonstration with A*
	A* Variants
	Applications of A* Search
Hill Climbing Search
Simulated Annealing
	The Traveling Salesman Problem (TSP)
	TSP Tour Representation
	Simulated Annealing Implementation
	Simulated Annealing Demonstration
Tabu Search
	Tabu Search Implementation
	Tabu Search Demonstration
	Tabu Search Variants
Constraint Satisfaction
	Graph Coloring as a CSP
	Scheduling as CSP
Constraint Satisfaction Problems
	Generate and Test
	Backtracking
	Forward Checking and Look Ahead
	Min-Conflicts Search
Chapter Summary
Algorithms Summary
References
Resources
Exercises
Chapter 4 AI and Games
Two Player Games
The Minimax Algorithm
	Minimax and Tic-Tac-Toe
	Minimax Implementation for Tic-Tac-Toe
	Minimax with Alpha-Beta Pruning
Classical Game AI
	Checkers
		Checker Board Representation
		Techniques used in Checkers Programs
			Opening Books
			Static Evaluation Function
			Search Algorithm
			Move History
			Endgame Database
	Chess
		Chess Board Representation
		Techniques used in Chess Programs
			Opening Book Database
			Minimax Search with Alpha Beta Pruning
			Static Board Evaluation
	Othello
		Techniques used in Othello Programs
			Opening Knowledge
			Static Evaluation Function
			Search Algorithm
			Endgames
			Other Algorithms
	Go
		Go Board Representation
		Techniques used in Go Programs
			Opening Moves
			Move Generation
			Evaluation
			Endgame
	Backgammon
		Techniques used in Backgammon Programs
			Neurogammon
			TD-Gammon
	Poker
		Loki - A learning Poker Player
	Scrabble
Video Game AI
	Applications of AI Algorithms in Video Games
		Movement and Pathfinding
			Table Lookup with Offensive and Defensive Strategy
		NPC Behavior
			Static State Machines
			Layered Behavior Architectures
			Other Action-Selection Mechanisms
		Team AI
			Goals and Plans
		Real-Time Strategy AI
			Rules-Based Programming
Chapter Summary
References
Resources
Exercises
Chapter 5 Knowledge Representation
	Introduction
	Types of Knowledge
	The Role of Knowledge
	Semantic Nets
	Frames
	Propositional Logic
		Deductive Reasoning with Propositional Logic
		Limitations of Propositional Logic
	First Order Logic (Predicate Logic)
		Atomic Sentences
		Compound Sentences
		Variables
		Quantifiers
		First-Order Logic and Prolog
			Simple Example
			Information Retrieval and KR
			Representing and Reasoning about an Environment
	Semantic Web
	Computational Knowledge Discovery
		The BACON System
		Automatic Mathematician
	Ontology
	Communication of Knowledge
	Common Sense
	Summary
	References
	Resources
	Exercises
Chapter 6 Machine Learning
	Machine Learning Algorithms
		Supervised Learning
			Learning with Decision Trees
				Creating a Decision Tree
			Characteristics of Decision Tree Learning
		Unsupervised Learning
			Markov Models
				Word Learning with Markov Chains
				Word Generation with Markov Chains
				Markov Chain Implementation
				Other Applications of Markov Chains
			Nearest Neighbor Classification
				1NN Example
				k-NN Example
	Summary
	Resources
	Exercises
		
Chapter 7 Evolutionary Computation
	Short History of Evolutionary Computation
		Evolutionary Strategies
		Evolutionary Programming
		Genetic Algorithms
		Genetic Programming
	Biological Motivation
	Genetic Algorithms
		Genetic Algorithm Overview
		Genetic Algorithm Implementation
	Genetic Programming
		Genetic Programming Algorithm
		Genetic Programming Implementation
	Evolutionary Strategies
		Evolutionary Strategies Algorithm
		Evolutionary Strategies Implementation
	Differential Evolution
		Differential Evolution Algorithm
		Differential Evolution Implementation
	Particle Swarm Optimization
		Particle Swarm Algorithm
		Particle Swarm Implementation
	Evolvable Hardware
	Summary
	References
	Resources
	Exercises
Chapter 8 Neural Networks I
Short History of Neural Networks
Biological Motiviation
Fundamentals of Neural Networks
	Single Layer Perceptrons
	Multi-Layer Perceptrons
	Supervised vs. Unsupervised Learning Algorithms
	Binary vs. Continuous Inputs and Outputs
The Perceptron
	Perceptron Learning Algorithm
	Perceptron Implementation
Least-Mean-Square (LMS) Learning
	LMS Learning Algorithm
	LMS Implementation
Learning with Backpropagation
	Backpropagation Algorithm
	Backpropagation Implementation
	Tuning Backpropagation
	Training Variants
	Weight Adjustment Variants
Probabilistic Neural Networks
	PNN Algorithm
	PNN Implementation
Other Neural Network Architectures
	Time Series Processing Architecture
	Recurrent Neural Network
Tips for Building Neural Networks
	Defining the Inputs
	Defining the Outputs
	Choice of Activation Functions
	Number of Hidden Layers
Chapter Summary
References
Exercises
Chapter 9 Neural Networks II
	Unsupervised Learning
	Hebbian Learning
		Hebb's Rule
		Hebb Rule Implementation
	Simple Competitive Learning
		Vector Quantization
		Vector Quantization Implementation
	k-Means Clustering
		k-Means Algorithm
		k-Means Implementation
	Adaptive Resonance Theory
		ART-1 Algorithm
		ART-1 Implementation
	Hopfield Auto-Associative Model
		Hopfield Auto-Associator Algorithm
		Hopfield Implementation
	Summary
	References
	Exercises
Chapter 10 Robotics and AI
	Introduction to Robotics
		What is a Robot?
		A Sampling from the Spectrum of Robotics
		Taxonomy of Robotics
			Fixed
			Legged
			Wheeled
			Underwater
			Aerial
			Other Types of Robots
		Hard vs. Soft Robotics
	Braitenburg Vehicles
	Natural Sensing and Control
	Perception with Sensors
	Actuation with Effectors
	Robotic Control Systems
	Simple Control Architectures
		Reactive Control
		Subsumption
		Other Control Systems
	Movement Planning
		Complexities of Motion Planning
		Cell Decomposition
		Potential Fields
	Group or Distributed Robotics
	Robot Programming Languages
	Robot Simulators
	Summary
	References
	Resources
	Exercises
Chapter 11 Robotics and AI
	Anatomy of an Agent
	Agent Properties and AI
		Rationale
		Autonomous
		Persistent
		Communicative
		Cooperative
		Mobile
		Adaptive
	Agent Environments
	Agent Taxonomies
		Interface Agents
		Virtual Character Agents
		Entertainment Agents
		Game Agents
		ChatterBots
			Eliza and Parry
			AIML
		Mobile Agents
		User Assistance Agent
			Email Filtering
			Information Gathering and Filtering
			Other User-Assistance Applications
		Hybrid Agent
	Agent Architectures
		What is Architecture?
		Types of Architectures
			Reactive Architectures
			Deliberative Architectures
			Blackboard Architectures
			BDI Architecture
			Hybrid Architectures
			Mobile Architectures
		Architecture Description
			Subsumption Architecture (Reactive)
			Behavior Networks (Reactive)
			ATLANTIS (Deliberative)
			Homer (Deliberative)
			BB1 (Blackboard)
			Open Agent Architecture (Blackboard)
			Procedural Reasoning System (BDI)
			Aglets (Mobile)
			Messengers (Mobile)
			SOAR (Hybrid)
	Agent Languages
		Telescript
		Aglets
		Obliq
		Agent TCL
		Traditional Languages
	Agent Communication
		Knowledge Query and Manipulation Language (KQML)
		FIPA Agent Communication Language
		Extensible Markup Language (XML)
	Summary
	Resources
	References
	Exercises
Chapter 12 Biologically Inspired and Hybrid Models
	Cellular Automata
		One Dimensional CA
		Two Dimensional CA
		Conway Application
		Turing Completeness
		Emergence and Organization
	Artificial Immune Systems
		Self-Management Capabilities
		Touchpoints
		Touchpoint Autonomic Managers
		Orchestrating Autonomic Managers
		Integrated Management Console
		Autonomic Summary
	Artificial Life
		Echo
		Tierra
		Simulated Evolution
			Environment
			The Bug (or Agent)
		Variations of Artificial Life
		Lindenmayer Systems
	Fuzzy Logic
		Introduction to Fuzzy Logic
		Fuzzy Logic Mapping
		Fuzzy Logic Operators
		Fuzzy Control
	Evolutionary Neural Networks
		Genetically Evolved Neural Networks
			Simulation Evolution Example
	Ant Colony Optimization
		Traveling Salesman Problem
			Path Selection
			Pheromone Intensification
			Pheromone Evaporation
			New Tour
		Sample Usage
		ACO Parameters
	Affective Computing
		Characterizing Human Emotion
		Synthesizing Emotion
	Resources
	
Chapter 13 The Languages of AI
	Language Taxonomy
		Functional Programming
		Imperative Programming
		Object Oriented Programming
		Logic Programming
	Languages of AI
		The LISP Language
			The History of the LISP Language
			Overview of the LISP Language
				Data Representation
				Simple Expressions
				Predicates
				Variables
				List Processing
				Programs as Data
				Conditions
				Functions in LISP
			LISP Summary
		The Scheme Language
			History of Scheme
			Overview of the Scheme Language
				Data Representation
				Simple Expressions
				Predicates
				Variables
				List Processing
				Conditions
				Iteration and Maps
				Procedures in Scheme
			Scheme Summary
		The POP-11 Language
			History of POP-11
			Overview of the POP-11 Language
				Data Representation
				Predicates
				Simple Expressions
				Variables
				List Processing
				Conditions
				Iteration and Maps
				Pattern Matching
				Procedures in POP-11
			POP-11 Summary
		Prolog
			History of Prolog
			Overview of the Prolog Language
				Data Representation
				List Processing
				Facts, Rules, and Evaluation
				Arithmetic Expressions
			Prolog Summary
	Other Languages
	Chapter Summary
	References
	Resources
	Exercises

Library of Congress Subject Headings for this publication:

Artificial intelligence -- Data processing.
Artificial intelligence -- Mathematical models.