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Chapter 14: Artificial Intelligence
Invitation to Computer Science,
Java Version, Third Edition
Invitation to Computer Science, Java Version, Third Edition 2
Objectives
In this chapter, you will learn about
A division of labor
Knowledge representation
Recognition tasks
Reasoning tasks
Robotics
Invitation to Computer Science, Java Version, Third Edition 3
Introduction
Artificial intelligence (AI) Explores techniques for incorporating aspects of
intelligence into computer systems Turing test
A test for intelligent behavior of machines Allows a human being to interrogate two entities,
both hidden from the interrogator A human being A machine (a computer)
Invitation to Computer Science, Java Version, Third Edition 4
Figure 14.1The Turing Test
Invitation to Computer Science, Java Version, Third Edition 5
Introduction (continued)
Turing test (continued)
If the interrogator is unable to determine which entity is the human being and which is the computer, the computer has passed the test
Artificial intelligence can be thought of as constructing computer models of human intelligence
Invitation to Computer Science, Java Version, Third Edition 6
A Division of Labor
Categories of tasks
Computational tasks
Recognition tasks
Reasoning tasks
Computational tasks
Tasks for which algorithmic solutions exist
Computers are better (faster and more accurate) than human beings
Invitation to Computer Science, Java Version, Third Edition 7
A Division of Labor (continued) Recognition tasks
Sensory/recognition/motor-skills tasks
Human beings are better than computers
Reasoning tasks
Require a large amount of knowledge
Human beings are far better than computers
Invitation to Computer Science, Java Version, Third Edition 8
Figure 14.2
Human and Computer Capabilities
Invitation to Computer Science, Java Version, Third Edition 9
Knowledge Representation
Knowledge: A body of facts or truths
For a computer to make use of knowledge, it must be stored within the computer in some form
Invitation to Computer Science, Java Version, Third Edition 10
Knowledge Representation (continued)
Knowledge representation schemes
Natural language
Formal language
Pictorial
Graphical
Invitation to Computer Science, Java Version, Third Edition 11
Knowledge Representation (continued)
Required characteristics of a knowledge representation scheme
Adequacy
Efficiency
Extendability
Appropriateness
Invitation to Computer Science, Java Version, Third Edition 12
Recognition Tasks
A neuron is a cell in the brain capable of
Receiving stimuli from other neurons through its dendrites
Sending stimuli to other neurons through its axon
Invitation to Computer Science, Java Version, Third Edition 13
Figure 14.4
A Neuron
Invitation to Computer Science, Java Version, Third Edition 14
Recognition Tasks (continued) If the sum of activating and inhibiting stimuli
received by a neuron equals or exceeds its threshold value, the neuron sends out its own signal
Each neuron can be thought of as an extremely simple computational device with a single on/off output
Invitation to Computer Science, Java Version, Third Edition 15
Recognition Tasks (continued) Human brain: A connectionist architecture
A large number of simple “processors” with multiple interconnections
Von Neumann architecture
A small number (maybe only one) of very powerful processors with a limited number of interconnections between them
Invitation to Computer Science, Java Version, Third Edition 16
Recognition Tasks (continued) Artificial neural networks (neural networks)
Simulate individual neurons in hardware
Connect them in a massively parallel network of simple devices that act somewhat like biological neurons
The effect of a neural network may be simulated in software on a sequential-processing computer
Invitation to Computer Science, Java Version, Third Edition 17
Recognition Tasks (continued) Neural network
Each neuron has a threshold value
Incoming lines carry weights that represent stimuli
The neuron fires when the sum of the incoming weights equals or exceeds its threshold value
A neural network can be built to represent the exclusive OR, or XOR, operation
Invitation to Computer Science, Java Version, Third Edition 18
Figure 14.5
One Neuron with Three Inputs
Invitation to Computer Science, Java Version, Third Edition 19
Figure 14.8
The Truth Table for XOR
Invitation to Computer Science, Java Version, Third Edition 20
Recognition Tasks (continued) Neural network
Both the knowledge representation and “programming” are stored as weights of the connections and thresholds of the neurons
The network can learn from experience by modifying the weights on its connections
Invitation to Computer Science, Java Version, Third Edition 21
Reasoning Tasks
Human reasoning requires the ability to draw on a large body of facts and past experience to come to a conclusion
Artificial intelligence specialists try to get computers to emulate this characteristic
Invitation to Computer Science, Java Version, Third Edition 22
Intelligent Searching
State-space graph
After any one node has been searched, there are a huge number of next choices to try
There is no algorithm to dictate the next choice
State-space search
Finds a solution path through a state-space graph
Invitation to Computer Science, Java Version, Third Edition 23
Figure 14.12
A State-Space Graph with Exponential Growth
Invitation to Computer Science, Java Version, Third Edition 24
Intelligent Searching (continued) Each node represents a problem state
Goal state: The state we are trying to reach
Intelligent searching applies some heuristic (or an educated guess) to
Evaluate the differences between the present state and the goal state
Move to a new state that minimizes those differences
Invitation to Computer Science, Java Version, Third Edition 25
Swarm Intelligence
Swarm intelligence Models the behavior of a colony of ants
Swarm intelligence model Uses simple agents that
Operate independently Can sense certain aspects of their environment Can change their environment May “evolve” and acquire additional capabilities
over time
Invitation to Computer Science, Java Version, Third Edition 26
Intelligent Agents
An intelligent agent: Software that interacts collaboratively with a user
Initially an intelligent agent simply follows user commands
Invitation to Computer Science, Java Version, Third Edition 27
Intelligent Agents (continued) Over time
Agent initiates communication, takes action, and performs tasks on its own using its knowledge of the user’s needs and preferences
Invitation to Computer Science, Java Version, Third Edition 28
Expert Systems
Rule-based systems
Also called expert systems or knowledge-based systems
Attempt to mimic the human ability to engage pertinent facts and combine them in a logical way to reach some conclusion
Invitation to Computer Science, Java Version, Third Edition 29
Expert Systems (continued)
A rule-based system must contain A knowledge base: Set of facts about subject
matter An inference engine: Mechanism for selecting
relevant facts and for reasoning from them in a logical way
Many rule-based systems also contain An explanation facility: Allows user to see
assertions and rules used in arriving at a conclusion
Invitation to Computer Science, Java Version, Third Edition 30
Expert Systems (continued)
A fact can be
A simple assertion
A rule: A statement of the form if . . . then . . .
Modus ponens (method of assertion)
The reasoning process used by the inference engine
Invitation to Computer Science, Java Version, Third Edition 31
Expert Systems (continued)
Inference engines can proceed through
Forward chaining
Backward chaining
Forward chaining
Begins with assertions and tries to match those assertions to “if” clauses of rules, thereby generating new assertions
Invitation to Computer Science, Java Version, Third Edition 32
Expert Systems (continued)
Backward chaining
Begins with a proposed conclusion
Tries to match it with the “then” clauses of rules
Then looks at the corresponding “if” clauses
Tries to match those with assertions or with the “then” clauses of other rules
Invitation to Computer Science, Java Version, Third Edition 33
Expert Systems (continued)
A rule-based system is built through a process called knowledge engineering
Builder of system acquires information for knowledge base from experts in the domain
Invitation to Computer Science, Java Version, Third Edition 34
Robotics
Robot: Device that can gather sensory information autonomously
Many uses for robots (auto manufacturing, bomb disposal, exploration, microsurgery)
Deliberative strategy: Robot has an internal representation of its environment
Reactive strategy: Uses heuristic algorithms to allow robot to respond directly to environment
Invitation to Computer Science, Java Version, Third Edition 35
Summary of Level 5
Level 5: Applications
Simulation and modeling
New business applications
Artificial intelligence
Invitation to Computer Science, Java Version, Third Edition 36
Summary
Artificial intelligence explores techniques for incorporating aspects of intelligence into computer systems
Categories of tasks: Computational tasks, recognition tasks, reasoning tasks
Neural networks simulate individual neurons in hardware and connect them in a massively parallel network
Invitation to Computer Science, Java Version, Third Edition 37
Summary (continued)
Swarm intelligence models the behavior of a colony of ants
Intelligent agent interacts with a user
Rule-based systems attempt to mimic the human ability to engage pertinent facts and combine them in a logical way to reach some conclusion
Robots can perform many useful tasks