Teaching

This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong.
====== Final Projects ======

RESEARCH CLUSTERS

Learning
  * Game AI - Luca*
  * Game AI - Daniel*
  * Machine Learning - Rahul
  * Image Rec - Momchil*

Simulation
  * Utility Theory - Jihee*
  * Flocking/simulation - Mara
  * Swarming Algorithms - Arkojit
  * Swarming Algorithms - David

Knowledge
  * Neural Nets - Connie*
  * Neural Nets - Mark
  * Big Data - Mark*
  * Big Data - Shreyas*

Human
  * Aerospace Robots - Alyanna*
  * Biocomputing - Fan*
  * Robotics - Anish
  * Robotics - Pranav*

Creativity
  * Algorithmic Music - Evan*
  * Algorithmic Music - Kevin*
  * Ethics - Shelby*
  * Story Generation- Kimberly*  


----


**Project Content**

You can work on one of a few types of projects. You can implement an algorithm or idea in class, investigate and report in depth on an existing implementation like Siri or Watson, or you can try something not discussed in the class.

The most important consideration is that you put significant time into your project. A great project will not only get you excited about your topic, but also get others excited about it.

Ideally, you will have some code written for your project, but you can also present pseudocode or just concepts.

For example, some of the most complete projects in previous years have involved people writing competing AIs for simple games or demonstrating interest applications of algorithms from class.

**Topics**

Find a topic that is interesting to you! We’ll get you in groups by Wednesday.
Your topic can be something from class, something you have heard about, or something unrelated.

**Topic List**

  * Algorithmic Music Composition
  * Autonomous Driving
  * Autonomous Agents
  * Bayesian Networks
  * Biocomputation
  * Chatbots
  * Chinese Room
  * Common Knowledge
  * Computational Creativity
  * Computer Vision
  * Decision Trees
  * Deep Learning
  * Ethical issues in AI
  * Expert Systems
  * Game Theory/Multi-Agents
  * General Game Playing
  * Genetic Algorithms
  * Haptics
  * Hidden Markov Model
  * Knowledge Ontologies
  * Knowledge Representation
  * Lisp
  * Motion Planning
  * Natural Language Processing
  * Natural Language Generation
  * Neural Networks
  * PageRank/Link Analysis
  * Player Models/Personality Models
  * Random Forests
  * Reinforcement Learning
  * Robot localization
  * Singularity
  * Siri
  * Speech Recognition
  * Supervised Learning
  * Swarm Algorithms
  * Story Generation
  * Turing Test
  * Video game AI
  * Watson
Teaching

User Tools

Site Tools

Page Tools
