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INVENTING THE FUTURE TEACHING GUIDE:
Smart Car

A car that could alert drivers to potential problems or wake up sleepyheads at the wheel seems like a futuristic fantasy, but the MIT Media Lab is working to make this dream a reality. The car's computer could recognize impending signs of trouble and help prevent accidents. Also in this segment, MIT's Professor Rosalind Picard talks about how she is teaching the computer to know how people are feeling. Part of her research includes learning more about the human brain.

 BIOLOGY cellular differentiation COMPUTER SCIENCE artificial intelligence MATH computers logic TECHNOLOGY computer simulations

One of the intriguing areas being explored in the field of Artificial Intelligence (AI) is Artificial Life. This field grapples with such questions as: How does a computer learn? Do machines evolve? And even, why do birds flock?

Scientists working with Artificial Life have devised a model they call "cellular automata" to understand living systems. This model states that behavior is based on a set of rules. Simply put, each cell determines its behavior based on what neighboring cells do.

Cellular automata is derived from automata theory, conceptualized in the 1950s as an abstract branch of mathematics to deal with automatic machines. Linguists and computer scientists became interested in the theory to explore the idea of thinking computers. Mathematician John von Neumann described cellular automata as mathematical "cells" -- like squares on a chessboard -- that change their state according to simple rules.

Experiments in this field help us synchronize traffic patterns and understand behavioral patterns in humans and animals. Cellular automata research has simulated biological processes and behaviors, including swarming and flocking behaviors and cellular differentiation.

The following activity uses a series of simple mathematical rules to demonstrate the concept of cellular automata. It uses eight students or cells because eight bits usually make up a byte in computer programs; a single character is usually made up of one byte.

In the following activity, read over the rules before starting. At the beginning, go slowly. While it may seem complicated at first, it will become easier as students learn the rules. Designate a leader to shout "go" before each change. You may want to rehearse the game with a group of eight students and present it as a class demonstration.

OBJECTIVE

Students will model cellular automata using simple rules and make connections to biological and mathematical systems.

PROCEDURE

Select eight students to stand in a circle with their backs to the outside. Students represent "cells" of information and will have two positions, standing or sitting. Each student will look at his/her neighbor on the right to determine what to do next based on these two rules:

• If the person to your right is up, sit down.
• If the person to your right is down, stand up.

Sound simple? Give it a try.

Start the circle in this configuration: D D D D D U D D

Each student looks to the right and makes a decision about what to do when the leader yells "go." All eight cells (students) make the change at the same time.

The second configuration should be: U U U U D U U U

Does every cell change? (No)

The third configuration should look like this: D D D U D D D D

Continue the process until the pattern begins to repeat.

TEACHER'S NOTE:

The pattern will begin to repeat after the eighth configuration. Try UUUUUUUU, UUDDUUDD or other combinations. The resulting oscillating pattern is called a "blinker."

CREDIT:

These activities and several others in this guide were developed by Kelly Wedding, biology teacher at Round Rock High School near Austin, Texas.

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