Algorithms, Combinatorics, and Optimization Theory Day Jointly Sponsored by DIMACS and Geogia Tech

October 24, 2009
Georgia Institute of Technology

Milena Mihail, Georgia Institute of Technology, mihail at
Vijay Vazirani, Georgia Institute of Technology, vijay.vazirani at
Presented under the auspices of the Special Focus on Discrete Random Systems.


Noga Alon, Tel-Aviv University

Title: Disjoint paths, isoperimetric problems, and graph eigenvalues

The spectral properties of a graph are intimately related to its structure. This can be applied in the study of discrete isoperimetric problems and in the investigation of extremal and algorithmic questions for graphs. I will discuss several recent examples illustrating this theme.

Manuel Blum, Carnegie Mellon University

Title: Can (Theoretical Computer) Science Get a Grip on Consciousness?

To come to grips with consciousness, I postulate that living entities in general, and human beings in particular, are mechanisms... marvelous mechanisms to be sure but not magical ones... just mechanisms. On this basis, I look to explain some of the paradoxes of consciousness such as Samuel Johnson's "All theory is against the freedom of the will; all experience is for it."

I will explain concepts of self-awareness and free will from a mechanistic view. My explanations make use of computer science and suggest why these phenomena would exist even in a completely deterministic world. This is particularly striking for free will.

The impressions of our senses, like the sense of the color blue, the sound of a tone, etc. are to be expected of a mechanism with enormously many inputs categorized into similarity classes of sight, sound, etc. Other phenomena such as the "bite" of pain are works in progress. I show the direction that my thinking takes and say something about what I've found and what I'm still looking for. Fortunately, the sciences are discovering a great deal about the brain, and their discoveries help enormously in guiding and verifying the results of this work.

Richard Karp, University of California at Berkeley

Title: What Makes an Algorithm Great

From time to time a new algorithm comes along that causes a sensation in theoretical computer science or in an area of application because of its resolution of a long-standing open question, its surprising efficiency, its practical usefulness, the novelty of its setting or approach, the elegance of its structure, the subtlety of its analysis or its range of applications. We will give examples of algorithms that qualify for greatness for one or more of these reasons, and discuss how to equip students to appreciate them and understand their strengths and weaknesses.

Mihalis Yannakakis, Columbia University

Title: Computational Aspects of Equilibria

Many models from a variety of areas involve the computation of an equilibrium or fixed point of some kind. Examples include Nash equilibria in games; price equilibria in markets; optimal strategies and the values of competitive games (stochastic and other games); stable configurations of neural networks; analysis of the evolution of various types of dynamic stochastic models. It is not known whether these problems can be solved in polynomial time. Despite their broad diversity, there are certain common computational principles that underlie different types of equilibria and connect many of these problems to each other. In this talk we will discuss some of these common principles and the corresponding complexity classes that capture them; the effect on the complexity of the underlying computational framework; and the relationship with other open questions in computation.

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Document last modified on October 5, 2009.