hw
MCB 419 - HW12 - Neural Q-Learning
due Tue Apr 30, 2019, 9:00 PM
email p5js project link to mcb419@gmail.com
Introduction
This week we combine reinforcement learning with neural networks. For this exercise, we will use a simple video game scenario, where the goal is to move a paddle left and right catch green pellets and avoid red pellets.
The important changes relative to hw11 are:
- the state space is now continuous, rather than discrete
- Q-values are estimated using a neural network, rather than a table
We follow the general approach given in this week’s reading assignment:
Mnih V, et al. (2015) Human Level Control Through Deep Reinforcement Learning. Nature 518, 539-533.
We will use the neural net library and reinforcement learning module documented here:
ConvNetJS: Deep Q Learning Demo
Instructions
- duplicate the HW12 template file
- follow instructions in the index.html file
- save and submit your project to mcb419@gmail.com with subject: HW12