## SSS Abstracts |

In a realizability model we take as true those statements which can be demonstrated by programs. A program which demonstrates a statement is called a `realizer' for the statement. We can think of realizers as evidence of a statement's truth. For example, an implication ``if A then B'' is considered true if there is a program that transforms evidence of A into evidence of B. Depending on what programs we take into account (do we allow parallel execution, exceptions, and timeouts?) we get different realizability models, each having its own set of valid rules of logic.

If we want to perform computations on mathematical objects, such as real numbers, differential equations, and topological spaces, we construct them by using the logic of a realizability model, and look at the realizers so obtained. They correspond to algorithms and data structures that best capture the nature of the desired mathematical objects.

As an example, I will show how the construction of real numbers in a realizability model suggests an implementation of arbitrary precision arithmetic. What we get is almost the IEEE floating point arithmetic. From this we draw the conclusion that IEEE almost got its floating point standard right.

I will present an interactive method for intuitive, hands-on control of rigid body motion. This technique relies on a simple extension of the traditional rigid body dynamics formulation. To change the motion, the artist freely manipulates the bodies at any point in time and the system computes the required physical parameters for the new motion. Although this method shows promise, it is still incomplete. I will address in detail the most difficult unresolved problem, which will be of special interest to those interested in machine learning, robot path planning and optimization over discrete domains.

Mobility introduces some significant constraints of its own --- mobile machines are severely constrained by the need to conserve battery power. Wireless network connectivity is often low-bandwidth, unreliable, and expensive in terms of both battery power and money.

In this talk, I will introduce the notion of multi-fidelity computations, and how they can help applications to operate within these resource constraints. I will then discuss my approach to providing operating system support for multi-fidelity applications.

But this cuts both ways: convincingly demonstrating that extracting such patterns is possible counts for empirical evidence against the efficient markets hypothesis. This has led to a line of economics research where machine learning techniques are used to find trading rules that produce beat the market consistently in out-of-sample data.

I will discuss the use of genetic programming to automatically discover these trading rules. Unfortunately, financial data is much noisier than datasets machine learning has traditionally been applied to. and this causes an shift of emphasis in the algorithm: instead of concentrating on search, understanding the representation and the data itself in relation to issues of overfitting is the key to success. Finally, I will discuss the idea of using text data in to supplement price data, and present some preliminary results using data collected from online stock chat boards.

My talk provides a brief history of how on-line community has been represented within models of Internet commerce. My research critically examines the arguments, narratives and rhetorical strategies drawn on within contemporary business texts to represent on-line community. It examines how the 'discourse of community' employed in these texts represents the possibilities of assembly, access, public use, and the control and ownership of knowledge produced by community members.

My talk provides a critique of some of the ways in which contemporary business models seek to commodify and privatize on-line community, and to police, order and regulate social interaction, cultural practices, community formation and knowledge production on-line. It also discusses why academics have an interest in involving themselves in helping organize alternative models of on-line community formation and knowledge production in the context of moves to corporatize and commodify higher education.

http://www.firstmonday.org/issues/issue4_9/werry/index.html

Link to related paper.