CS81 — Adaptive Robotics
Spring 2014

Goals | Grading | Paper Summaries | Schedule | Final papers

This syllabus is an active document. Please be aware that course schedule will change throughout the semester; you should review the schedule weekly.

Class information

Room: Science Center 252 aka "the robot lab"
Section 1: T, TH 9:55–11:10am
Section 2: T, TH 11:20–12:35pm
Lab A: W 1:15–2:45
Lab B: W 3:00–4:30

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


This seminar will explore the topic of adaptive robotics with a focus on developmental robotics, a newly emerging paradigm of research. The goal of developmental robotics is to create intelligent robots by allowing them to go through a developmental process, rather than being directly programmed to solve a particular task. By endowing a robot with an appropriate initial control architecture and adaptive mechanisms, it can learn through interactions with the world, developing self-organized knowledge about itself and its environment. We will be studying the following sorts of questions: What should be innate in the robot? What adaptive mechanisms are needed? What motivates the robot to act?

Goals for the course


Paper Summaries

Read all of the papers for the week prior to class on Tuesday. Bring a typed summary of the papers with you to class on Tuesday. You will turn this in at the end of class on Tuesday. I will write comments on it and return it to you at the start of class on Thursday.

For each paper include the following:


1 Jan 21   Introduction and Neural computation
  • Chapters 1-2 from Computational Developmental Psychology, Thomas Schultz (1995).
pyrobot overview
Lab 1: Neural network brains for robots
Jan 23  
Jan 28   Evolutionary robotics Lab 2: Evolving neural network brains for robots
Jan 30 Drop/Add ends (Jan 31)
Feb 04   Novelty search Lab 3: Novelty search
Feb 06  
Feb 11   Developmental robotics
  • Developmental Robotics: From Babies to Robots, by Cangelosi and Schlesinger (In press), Chapters 1-2
Lab 4: Scribbler robot
Feb 13  
Feb 18   Intrinsic motivation Midterm project
Feb 20  
Feb 25   Unsupervised learning CheckPoint Presentations on midterm project
Feb 27  
Mar 04   Imitation learning Finish midterm project
Mar 06 Midterm project due at 3pm (Mar 07)

Mar 11

Spring Break

Mar 13

Mar 18   Reinforcement learning Lab 5: The Horde

Mar 20  
Mar 25   Developmental encodings Lab 6: Compositional pattern producing networks
Mar 27 Last day to declare CR/NC or W (Mar 28)
Apr 01   Papers selected by students
Final project

Apr 03  
Apr 08   Papers selected by students
Work on final project
Apr 10  
Apr 15   Checkpoint presentations
Apr 17  
Apr 22   Papers selected by students
Apr 24  
Apr 29   Presentations
May 01 Final project due at 3pm (May 09)

Final papers