Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

17
Computational Representation of Ant Foraging Clayton Lewis June 26, 2010

description

Explore Run the complete simulation, and see what features of the behavior of the simulated ants you can identify. At this stage, don’t examine the rules, or modify simulation properties. Run the simulation fairly slowly at first so as to be able follow the behavior of individual ants. Think about the brown markings as trails, not tunnels.

Transcript of Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Page 1: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Computational Representation of Ant Foraging

Clayton LewisJune 26, 2010

Page 2: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Find and Download the “Ants” Simulation

• from the scalable game design home page, – click “Summer Institute 2010”– then “STEM Simulations”– then “Ants”– then “complete” to download Agentsheets

Project

Page 3: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Explore

• Run the complete simulation, and see what features of the behavior of the simulated ants you can identify.

• At this stage, don’t examine the rules, or modify simulation properties.

• Run the simulation fairly slowly at first so as to be able follow the behavior of individual ants.

• Think about the brown markings as trails, not tunnels.

Page 4: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Discussion

• How do these behaviors of the simulated ants compare to those of real ants?

Page 5: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Thought Questions about Real Ants

• How do they find their way back to the nest?

• Why could it be useful for the trail pheromone to evaporate?

Page 6: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Exploring Variations

• The simulation property “ticks” measures how quickly the ants have exhausted the food.

• The simulation property “turning” controls how often ants turn when foraging

• Let’s use these properties to explore what value of turning works best

Page 7: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Exploring Turning

• We’ll create a simple food layout• Use the arrow tool and move the nest to the

middle of the worksheet• Erase the food• Place 4 lollipops a little way NE,SE,SW, and

NW of the nest• Erase the ants and put 4 in next to the nest,

E,S,W,N• SAVE the worksheet

Page 8: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Exploring Turning (Cont.)

• We’ll assign values of “turning” by counting off: 10,50,90

• Reset your simulation• Set the value of turning to your value in

the Simulation Properties Window• Run the simulation• Report the value of ticks when all the

food is gone

Page 9: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

What is the best turning value?

Page 10: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Exploring Turning (Cont.)

• Let’s change food layout• Use the arrow tool and move the food near

the corners of the worksheet• SAVE

• Check that your simulation properties window shows your value of turning, and ticks 0

• Run the simulation again with your value of turning

Page 11: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

What is the best turning value?

Page 12: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

More Explorations

What is the effect of pheromone life? Does it depend on the amount of food at a food site?

Does this effect depend on number of foragers?

Does the optimal turning value depend on the number of foragers?

Page 13: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Actual Ant Turning is Density Dependent (Gordon, 1999)

Page 14: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

About the Program

• The program uses several computational thinking patterns:– collision (ant and food)– diffusion (distance to nest)– hillclimbing (to find nest)– polling (to control ticks)

• These and many others are described on the Wiki

Page 15: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Extending/Changing the Program

• What if there is no pheromone trail?– (Try it… first find the rule that places the trail… a

little tricky!)• The ants don’t follow the trail perfectly… can

you (or your students) improve this?• Some real ants don’t begin to search until

they have moved some distance straight from the nest…(why?) … could you add this feature?

Page 16: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Ant Tournament

• Students can be challenged to produce improved ants that forage more quickly

• …and to research how their improvements relate to real ant foraging

Page 17: Computational Representation of Ant Foraging Clayton Lewis June 26, 2010.

Final Words

• Real ant researchers use simulations to understand ant behavior…

• … and some computer scientists study ants to understand new ways of searching for information.

• More ant materials are on the Wiki