====== Welcome to Fall 2016 16.410/13: Introduction to Autonomy and Decision Making ======

This wiki will contain useful information for the course.

===== Useful Links =====

  - [[https://stellar.mit.edu/S/course/16/fa16/16.410/|Stellar Page]]
  - [[https://piazza.com/class/irm6tyo9mlr7ee|Piazza Forum]]


===== Course Logistics =====

**Classes:** MW 9:30-11am in 33-419

**Recitations:** F11 or F3 in 33-419. First recitation on Friday 09/09.

In a nutshell:

  * Weekly python/handwritten problem sets.
  * Midterm
  * Course Project (only for 16.413 students)
  * Final

Please refer to the Course Policies PDF in Stellar for further information.

===== Quick Start Guide to the course software and Problem Set 1 =====

  - [[vm_documentation|Install the course virtual machine]]
  - [[jupyteripython_documentation|Read about the Jupyter/IPython notebook]] that we'll use in our problem sets
  - Start working on [[psets:pset1|Problem Set 1]]

===== Problem Sets =====

Links to problem set pages will be posted here as they are released. Remember, problem sets may have **handwritten components** in addition to coding. Be sure the read the assignment carefully.

  * [[psets:pset1|Problem Set 01]] (**due on 09/14**)
===== Project (16.413 students only) =====

Links to project pages will be placed here when they are released.

  * [[projects:project1|Project 01]] (**due on 10/26**)
  * [[projects:project2|Project 02]] (**due on 11/23**)



===== Documentation =====

The following links contain work in progress documentation. We'll update the following links and add more content as the course progresses.

  * [[vm_documentation|Course Virtual Machine (Installation and how to use)]]
  * Jupyter/IPython notebook
    * [[jupyteripython_self_installation|Self installation without the VM (unsupported method)]]
    * [[jupyteripython_documentation|Documentation/tips]]
  * [[psets:pset_submission|Submitting Python Problem Sets]]
  * [[ff_planner|Using the FF activity planner]]
  * [[numberjack|Using Numberjack: a CSP modeling tool for python]]

===== References =====

==== Textbooks ====
  * [AIMA] **“Artificial Intelligence: A Modern Approach”**,  by S. Russell and P. Norvig (Prentice Hall),  3rd Edition. 
  * [PA] “Planning Algorithms,” by S. LaValle (Cambridge Press), available at http://planning.cs.uiuc.edu/
  * [IOR] “Introduction to Operations Research,” by F. S. Hillier and G. J. Lieberman (McGraw-Hill).

Of these books, the most relevant for this course is “Artificial Intelligence: A Modern Approach”,  by S. Russell and P. Norvig. None of these books are required, but this one is nice to have, as it's a good general purpose AI reference. The latest edition is the 3rd, from 2009. The 2nd edition is older (2003) and there are significant changes between both. The core algorithms haven't changed, but the newer edition contains more information about recent advancements.
==== Python ====

In this course we'll still be using Python2.7 to ensure compatibility with all the software we are using. If you read books or tutorials on Python, make sure they are for Python2 as there are breaking changes between Python2 and Python3.

  * [[http://learnpythonthehardway.org/book/index.html|Learn Python the Hard Way]]
    * A popular online Python2 book aimed at beginners
  * [[http://www.swaroopch.com/notes/python/|A Byte of Python]]
    * Another popular Python2 online book.
  * [[http://introtopython.org|Introduction to Python]]
    * An interactive online Python2/3 tutorial. Note that it was made using the Jupyter notebook, and that you have the example notebooks for this book in the VM (''example_notebooks/Learning/intro_programming/notebooks'')