No office hours today (EECS faculty meeting) or next Tuesday (Coll. of Engineering
Strategic Planning Meeting). If you need to see me, please send email to set up an
appointment.
Exam II will be Apr. 27. There will be a review session before it (TBA).
Artificial Intelligence (AI):
Many important programming techniques (including much of OOP) were originally
developed for AI, and then found to be useful in other application areas. AI
techniques have been exported to other applications.
Definition: AI is the art of getting computers to do things that, if they were done by
a human, would be considered intelligent.
(Some AI researchers complain that as soon as they get computer to do something
smart, it's not considered AI any more.)
Examples of AI: language use, logic, problem solving, mathematics, playing board
games, etc. (In most cases non-human animals cannot do these things, so they
were considered especially characteristic of human intelligence.)
This is a more application-oriented definition of AI than that provided by, for
example, the Turing Test, which considers a definitive test of AI to be that the
computer can fool a human into thinking that the computer is a human.
Notice that all of these examples of AI are intellectual activities, since these have
been considered characteristic of human intelligence. This is what a lot of AI
research has concentrated on. Historically AI has neglected other intelligent
activities, such as pattern recognition (face recognition), sensory-motor
coordination, and many body-centered kinds of intelligence (much of which we
share with other animals).
All of the above (intellectualist or symbolic approach) is sometimes called GOFAI =
Good Old-Fashioned AI.
Recently (in the past 20 years), there's been a shift of attention from "thinking
machines" to embodied intelligence (which make use of the physical body as an
adjunct to what the brain is doing).
Part of this change has been the discovery that the higher-level kinds of intelligence
build and depend on the lower kinds of intelligence, as a foundation. For example,
the manipulation of formulas makes use of some of the same pattern-matching
abilities that we use for recognizing physical objects. This is a more bottom-up
approach.
Newer approaches include connectionism, neural nets, and embodied AI.
This chapter presents two examples of GOFAI. We explore how to program playing
a board game intelligently. These techniques can be used in many other situations
where we're trying to plan the best course of action.
Board game playing is a good test case for GOFAI, because it involves intellectual
activities like planning, developing strategies, decision making, etc.
Tic-tac-toe game:
In ch. 10 we have an iterative refinement of the game:
(1) Get the program to play the game legally.
(2) Get the program to play the game intelligently.
We need some sort of representation of the board inside the computer. There are
many ways to do this (e.g., 3x3 matrix of characters), but it's simpler in this case to
just use a vector of nine characters, in the order:
012
345
678
Nevertheless, it's useful abstraction to give this data type an application oriented
name:
typedef vector <char> Board;
/* This makes "Board" a synonym for "vector
<char>" */
How do you tell if there is a winning board position?
Remember: "If you pick the right data structure, the algorithm will design itself."
In this case, the WINS matrix is used to represent all the winning configurations.
// These square triples represent wins (three in a row).
int WINS[][3] = {{0, 1, 2},{3, 4, 5},{6, 7, 8},
// the rows
{0, 3, 6},{1, 4, 7},{2, 5, 8},
// the columns
{0, 4, 8},{2, 4, 6}};
// diagonals
You know you can represent a 2D matrix as a vector of vectors. In this case we are
representing a 2D matrix as a C-array of C-arrays (we are using C-arrays because
they are easier to initialize).
The definition means that WINS is a matrix with "enough" rows and 3 columns to
hold the initialization data. In this case there are 8 rows.
The above declaration in effect declares the matrix:
WINS =
012
345
678
036
147
258
048
246
To have a winning configuration, we have to have the same non-blank character
(either 'X' or 'O') in board positions
WINS[k][0], WINS[k][1], and WINS[k][2], for some k between 0 and 8.
Heuristic = a rule of thumb that is not guaranteed to work. In this program
evaluate() is the heuristic.