- HW 01 (due Tu, Jan 22, 9pm)
peer assessment due by Th 9pm
Intro; basic foraging
- HW 02 (due Tu, Jan 29, 9pm)
Movement strategies
- HW 03 (due Tu, Feb 05, 9pm)
Braitenberg vehicles
- HW 04 (due Tu, Feb 12, 9pm)
Threshold logic
- HW 05 (due Tu, Feb 26, 9pm)
Action selection I
- HW 06 (due Tu, Mar 05, 9pm)
Action selection II
- HW 07 (due Tu, Mar 12, 9pm)
Spike-based coding
- HW 08 (due Tu, Apr 02, 9pm)
Associative learning -
- HW 09 (due Tu, Apr 09, 9pm)
Spatial navigation
- HW 10 (due Tu, Apr 16, 9pm)
Reinforcement learning
- HW 11 (due MON, Apr 22, 9pm)
Bot-challenge game design
- Final Proj (MON, Apr 29, 9pm)
Bot-challenge final
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Homework
MCB 419 Homework 4
This week's model explores threshold-logic ideas introduced by Braitenberg
in Vehicle 5. The 'on-off' non-linearity allows 'neurons' to make
'decisions' that influence behavior.
In this week's scenario, the bot is faced with a foraging task where it has to make
a few key decisions to optimize performance (to move, or not to move... to open its mouth, or keep it shut...).
First you'll explore the behavior generated by a controller that uses 5 threshold-logic 'neurons'
to solve the task.
Then you'll write a controller using regular 'ifelse' NetLogo syntax
to see if you can do better.
Template: hw04_template.nlogo
Solution file:
hw04_sample_solution.nlogo
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