1. Invitation to Computer Science 5th Edition
Chapter 15
Artificial Intelligence

2. Objectives In this chapter, you will learn about: A division of labor
Knowledge representation
Recognition tasks
Reasoning tasks
Robotics
Invitation to Computer Science, 5th Edition

3. Introduction Artificial intelligence (AI) Turing test
Explores techniques for incorporating aspects of intelligence into computer systems
Turing test
Allows a human to interrogate two entities, both hidden from the interrogator
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4. Figure 15.1 The Turing Test
Invitation to Computer Science, 5th Edition

5. A Division of Labor Computational tasks Adding a column of numbers
Sorting a list of numbers into numerical order
Searching for a given name in a list of names
Managing a payroll
Calculating trajectory adjustments for the space shuttle
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6. A Division of Labor (continued)
Recognition tasks
Recognizing your best friend
Understanding the spoken word
Finding the tennis ball in the grass in your backyard
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7. A Division of Labor (continued)
Reasoning tasks
Planning what to wear today
Deciding on the strategic direction a company should follow for the next five years
Running the triage center in a hospital emergency room after an earthquake
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8. Figure 15.2 Human and Computer Capabilities
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9. Knowledge Representation
Language schemes
Natural language
Formal language
Pictorial
Graphical
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10. Figure 15.3 A Semantic Net Representation
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11. Knowledge Representation (continued)
Characteristics of knowledge representation scheme
Adequacy
Efficiency
Extendability
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12. Recognition Tasks Neuron Artificial neural networks
Cell capable of receiving stimuli, in the form of electrochemical signals, from other neurons through its many dendrites
Can send stimuli to other neurons through its single axon
Artificial neural networks
Can be created by simulating individual neurons in hardware and connecting them in a massively parallel network of simple devices
Invitation to Computer Science, 5th Edition

13. Figure 15.4 A Neuron
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14. Figure 15.5 One Neuron with Three Inputs
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15. Figure 15.6 Neural Network Model
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16. Figure 15.7 A Simple Neural Network - OR Gate
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17. Figure 15.8 The Truth Table for XOR
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18. Figure 15.9 An Attempt at an XOR Network
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19. Recognition Tasks (continued)
Neural network
Can learn from experience by modifying the weights on its connections
Can be given an initial set of weights and thresholds that is simply a first guess
Network is then presented with training data
Back propagation algorithm
Eventually causes the network to settle into a stable state where it can correctly respond to all inputs in the training set
Invitation to Computer Science, 5th Edition

20. Reasoning Tasks Characteristic of human reasoning
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, 5th Edition

21. Intelligent Searching
Decision tree for a search algorithm
Illustrates the possible next choices of items to search if the current item is not the target
Decision tree for sequential search is linear
Classical search problem benefits from two simplifications
Search domain is a linear list
We seek a perfect match
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22. Figure 15.10 Decision Tree for Sequential Search
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23. Figure 15.11 Decision Tree for Binary Search
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24. Figure 15.12 A State-Space Graph with Exponential Growth
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25. Intelligent Searching (continued)
Solution path
Takes us from the initial state to a winning configuration, and the graph nodes along the way represent the intermediate configurations
Brute force approach for a solution path
Traces all branches of the state-space graph
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26. Swarm Intelligence Swarm intelligence model Uses simple agents that:
Operate independently
Can sense certain aspects of their environment
Can change their environment
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27. Intelligent Agents Intelligent agent Examples
Software technology designed to interact collaboratively with a user somewhat in the mode of a personal assistant
Examples
Personalized Web search engine
Web searcher that enables you to “vote” on each article it sends you
Online catalog sales company that uses an agent to monitor incoming orders and make suggestions
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28. Expert Systems Rule-based system Modus ponens
Attempts to mimic the human ability to engage pertinent facts and string them together in a logical fashion to reach some conclusion
Must contain these two components
A knowledge base
An inference engine
Modus ponens
Gives us a method for making new assertions
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29. Expert Systems (continued)
Forward chaining
Begins with assertions and tries to match those assertions to the “if” clauses of rules
Backward chaining
Begins with a proposed conclusion and tries to match it with the “then” clauses of rules
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30. Expert Systems (continued)
Explanation facility
Allows the user to see the assertions and rules used in arriving at a conclusion
Knowledge engineering
Requires interaction with the human expert, much of it in the domain environment
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31. Robotics
Uses for robots in manufacturing, science, the military, and medicine
Assembling automobile parts
Packaging food and drugs
Placing and soldering wires in circuits
Bomb disposal
Welding
Radiation and chemical spill detection
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32. Robotics (continued) Two strategies characterize robotics research
Deliberative strategy: says that the robot must have an internal representation of its environment
Reactive strategy: uses heuristic algorithms to allow the robot to respond directly to stimuli from its environment
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33. Summary Artificial intelligence Categories of tasks Neural networks
Explores techniques that incorporate aspects of intelligence into computer systems
Categories of tasks
Computational, recognition, and reasoning
Neural networks
Simulate individual neurons in hardware and connect them in a massively parallel network
Invitation to Computer Science, 5th Edition

34. 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
Invitation to Computer Science, 5th Edition