CS 5973: Neuro/Cognitive Projects

The semester-long project constitutes a significant percentage of your class grade. Projects will be experimental in nature, requiring a carefully-designed computational hypothesis, a computer implementation, an experiment, and an analysis of the results. Project topics must be based on a set of at least three papers drawn from the literature; one of these papers must be drawn from the set of papers on the course schedule page. With approval, students may collaborate on projects in groups of size two. In these projects, it must be clear that there is a significant and differentiable contribution that can be made by each student.

For those students who do not have a significant background in programming, we will make every effort to design an appropriate collaborative project.

All project-related materials must be handed in on the specified due date: for in-class presentations, you must be ready to present in class; written materials are due at 23:59. Written materials may be handed in via email or the course blackboard.


Project Proposal

The proposal should answer:

Project Ideas

Grounding Symbols for Color Descriptions

Spatial Concept Grounding from Visual Examples

This project would play out in a manner that is similar to the color grounding problem. In this case, however, we would like to construct spatial models of concepts such as "left of," "on top of," and "near."

Instead of constructing models in color space, we would construct models that capture spatial relationships. Gaussians (or mixtures thereof) could also be used (although there might be some other distributions that do a better job).

Interaction of the Dorsal and Ventral Visual Pathways

We understand a fair amount about the roles played by the dorsal and ventral visual pathways. However, much less is understood about how these pathways might interact with one-another. Several of the papers on the reading list represent different aspects of how the dorsal/ventral computations may take place individually, and in some cases examine how their interaction might play out. These include:

Model of Development: Choosing which Skills to Learn and When

Many approaches to skill learning are focused on learning an individual skill (i.e, have a single reward function). In the rare case in which a set of skills is learned, it is typically the experimenter that determines the sequence in which the skills are learned. In contrast, infants and toddlers are constantly "hopping" from one learning problem to another -- in many cases, this process of switching between learning tasks is determined internally. What is it that drives this selection of learning task? We know that selection cannot be arbitrary: many skills build on top of others that have been previously learned, and (early in the process) the developing body does not have the motor strength or representational capability to take on the more complicated tasks. One computational theme that we see in a variety of writings (see the curiosity and development section of the schedule) is that of focusing on areas of "moderate novelty." This means that the agent actively seeks out experience in the world in which some success has already been found, but that high performance has yet to be achieved.

For a class project, one could implement one such mechanism of development.

Recognition of Grasping Actions

Given a time series of hand position, orientation, and shape, how can an observing agent extract a deep representation of the grasping action? In particular, we would like to extract the goal of the reach (which includes the object identity and the how the object is to be grasped). Depending upon the application, we may want to be able to produce a prediction of the goal before the hand actually arrives at the object. In other applications, we may wish to label a sequence of pick-and-place operations after the fact.

There are a number of computational theories that attempt to explain this recognition process. Some of the most interesting are inspired by Rizzolatti's mirror cell work which suggests that the control system itself is involved in the recognition process.

Hardware Access

Some of my robot hardware is available for use in your projects. In addition, some of my students are available to help in the data collection process.

Final Project Document

Project Presentation

Your final project presentation constitutes 10% of your course grade. At the time of your presentation, your experiments should be complete. You will have a total of 30 minutes to present your project and to address questions (so plan on 25 minutes of material). Your slides should cover:

fagg AT ou.edu

Last modified: Sat Dec 3 19:31:09 2005