CS81 — Adaptive Robotics
Fall 2017

Goals | Grading | Accommodations | Paper Responses | Schedule

Class information

Class: T, TH 1:15–2:30 SCI L26
Lab A: M 1:15–2:45 SCI 256
Lab B: M 3:00–4:30 SCI 256

Professor: Lisa Meeden
Office: Science Center 243
Phone: 328-8565

Introduction

This seminar will examine ways of making robots be more adaptive. We will investigate methods that allow robots to learn about themselves and their environment by autonomously exploring what they can achieve rather than being told how to behave. We will focus on machine learning approaches including evolutionary robotics, developmental robotics, unsupervised learning, reinforcement learning, and deep learning. This is a discussion-based course that relies on students doing a close reading of assigned research papers and coming to class prepared to actively engage with the material.

Goals for the course

Grading

Accommodations

If you believe that you need accommodations for a disability, please contact the Office of Student Disability Services (Parrish 113W) or email studentdisabilityservices@swarthmore.edu to arrange an appointment to discuss your needs. As appropriate, the Office will issue students with documented disabilities a formal Accommodations Letter. Since accommodations require early planning and are not retroactive, please contact the Office of Student Disability Services as soon as possible. For details about the accommodations process, visit the Student Disability Service Website.

You are also welcome to contact me privately to discuss your academic needs. However, all disability-related accommodations must be arranged through the Office of Student Disability Services.

Paper Responses

Each class meeting will typically focus on one paper. Prepare for class by reading the assigned paper and writing a response in the format described below.




Schedule

WEEK DAY ANNOUNCEMENTS TOPIC & READING LAB
1

Sep 05

  Introduction to Adaptive Robotics and Neural Networks 1: Simulating Robots in Jupyter Notebooks

Sep 07

 
2

Sep 12

  Developmental Robotics 2: Neural Network Robot Controllers

Sep 14

 
3

Sep 19

Bryce Wiedenbeck Guest lecturer

No lab
Lisa attending EpiRob17 Conference

Sep 21

Frank Durgin Guest lecturer

4

Sep 26

Read Sections 1-3

Evolving Neural Networks3: Evolving Neural Network Controllers

Sep 28

Read Sections 4-7

5

Oct 03

  Novelty-based vs Objective-based Evolution 4: Implementing Novelty Search

Oct 05

 
6

Oct 10

  Reading from Melanie Mitchell 5: Applying Novelty Search

Oct 12

Melanie Mitchell Guest lecturer

 

Oct 17

Fall Break

Oct 19

7

Oct 24

  Intrinsic Motivation 6: Creating a Research Poster

Oct 26

 
8

Oct 31

  Unsupervised Learning Begin Final Project

Nov 02

 
9

Nov 07

  Reinforcement Learning Discuss Project Proposal

Nov 09

 
10

Nov 14

  Deep Learning Continue Project

Nov 16

 
11

Nov 21

  Checkpoint Demonstrations Checkpoint Demonstrations

Nov 23

Thanksgiving

12

Nov 28

  CS Research Talks
Project Presentations
Continue Project

Nov 30

 
13

Dec 05

  Project Presentations Project Presentations

Dec 07

 
14

Dec 12

  No lab