2. Chapter 13: Artificial Intelligence Chapter 13 Artificial Intelligence Page 139 Computations that make it possible for a machine to perceive, reason, and act in a manner consistent with human behavior form the field known as artificial intelligence. The Turing Test A human questioner inputs questions and guesses which respondent is human, based on the answers given. If the questioner cannot tell which respondent is human, the software passes the test.

3. Computer Reasoning Chapter 13 Artificial Intelligence Page 140 To simulate logical reasoning, heuristic functions are often used. A heuristic is an artificial measure of how close the computer’s current status is to its problem-solving goal. In the tic-tac-toe example above, when the computer is ready to make an X-move, it uses the heuristic max{F(config), where config can be the result of any O-move}. F(config) = (# of completable rows, columns, and diagonals for X-player) – (# of completable rows, columns, and diagonals for O-player) if config is a non-winning configuration  if config is an X-win ---- if config is an O-win OO X X XOO X X XOO OX X XOO X XO XOO X XO XOO XO X 2-1=13-1=22-1=13-1=2 OO XX X OOO XX X OO XX XO OO XX XO OO XXO X -- 3-2=12-2=03-2=1 OO X XX OOO X XX OO OX XX OO X XXO OO XO XX -- 2-2=0 3-2=1 OO XX X OOO XX X OO OXX X OO XX XO OO XX XO -- 2-1=1 OO X XX OOO X XX OO OX XX OO X XOX OO XO XX -- 3-1=2 1 -- -- -- --

4. Expert Systems Chapter 13 Artificial Intelligence Page 141 By programming a computer with the assistance of experts in a particular field, an expert system can be developed to perform very specialized tasks. Users in need of expert assistance complete on-line questionnaires and the expert system analyzes their responses and assigns probabilities to various diagnoses.

5. Neural Networks Chapter 13 Artificial Intelligence Page 142 To simulate learning, certain multiprocessor systems, called neural networks, have been built to “learn” to recognize particular patterns as correct or incorrect, based upon a trial-and-error process. In the example below, a neural network is used to teach a computerized system how to back a truck up to a loading dock. The physical characteristics of the truck are programmed, with the relationship between the steering wheel, the tires, the cab, and the trailer formally calculated. Starting at some initial position, the truck is backed up one meter at a time, with programmed steering; the error in the result is measured and factored into the next attempt, until the error is zero.

6. Natural Language Processing Chapter 13 Artificial Intelligence Page 143 Written Comprehension: How can a computer be programmed to grasp the syntax and semantics of a natural language? John saw the boy in the park with the telescope. Question: Whose telescope is it? Answer: John’s John saw the boy in the park with the puppy. Question: Whose puppy is it? Answer: The boy’s John saw the boy in the park with the statue. Question: Whose statue is it? Answer: The park’s

7. Speech Recognition Chapter 13 Artificial Intelligence Page 144 0011010101000 0101111101010 0100110101010 0101011110010 1011010100110 1010101010101 0101010101001 1.The PC sound card converts analog sound waves spoken into a microphone into a digital format. 2.A software acoustical model breaks the word into phonemes. 0011010101000 “K” 0101111101010 “AH” 0100110101010 “M” 0101011110010 “P” 1011010100110 “Y” 1010101010101 “OO” 0101010101001 “T” 3.A software language model compares the phonemes to words in its dictionary. “K”“AH”“M”“P”“Y”“OO”“T” CALM COMMA COMPARE COMPETE COMPLETE COMPUTE 4.Once the software decides on the most likely candidate, it displays that word. COMPUTE

8. Robotics Chapter 13 Artificial Intelligence Page 145 Robots are programmable devices capable of manipulating objects and performing tasks much like humans are able to do. One of the more difficult problems when programming a robot is determining when it is about to collide with something, when it has collided with something, and what to do in response to a collision. Collision Avoidance Use scanners to determine the robot’s proximity to other objects, redirecting the robot when a collision is imminent. Collision Detection Use sensors at strategically located places on the robot to determine if a collision occurs. Collision Reaction Go around? Climb over? Bounce back? Run away? Drop dead?

9. Robot Challenges Chapter 13 Artificial Intelligence Page 146 Other common human actions that are difficult to program include propelled locomotion and manual manipulation. Walking Gait How can a robot be programmed to propel itself forward on “legs” and still maintain its balance? Grasping How can a robot be programmed to grasp part of a stack of objects, without toppling the rest of the stack?

10. AI in Games Chapter 13 Artificial Intelligence Page 147 Non-player characters in games need to appear intelligent, even though they are controlled by the game program instead of by a game player. Flocking By providing a group of characters with simple goals and behaviors, a “mob mentality” can be implemented with a minimum of code. Dead Reckoning By having a game-driven predator character react to the anticipated position of its player-driven prey (using the prey’s current position and velocity), a chase can appear more realistic.