[PRL] Fwd: [Econcs] [Econcs-general] Friday 09/19: Karl Lieberherr on Effective Organization of a Motivated Community to Obtain Effective Algorithmic Solutions

Karl Lieberherr lieber at ccs.neu.edu
Mon Sep 15 21:31:10 EDT 2014


I am giving a talk at Harvard on Ahmed's Dissertation and follow-up work.
-- Karl

---------- Forwarded message ----------
From: Thibaut Horel <thibaut.horel at gmail.com>
Date: Mon, Sep 15, 2014 at 9:21 AM
Subject: [Econcs] [Econcs-general] Friday 09/19: Karl Lieberherr on
Effective Organization of a Motivated Community to Obtain Effective
Algorithmic Solutions
To: econcs-general at eecs.harvard.edu


Hi all,

This week, Karl Lieberherr <http://www.ccs.neu.edu/home/lieber/> from
Northeastern University will give us a talk on Effective Organization of a
Motivated Community to Obtain Effective Algorithmic Solutions.

*Who: *Karl Lieberherr (Northeastern University)
*Where:* Maxwell-Dworkin 123 at 33 Oxford St, Cambridge, MA 02138
*When:* Friday, September 19th, 1:45pm-3:30pm (talk starts at 2pm)
*Title:* Effective Organization of a Motivated Community to Obtain
Effective Algorithmic Solutions
*Abstract:*

We introduce a new game, called side-choosing game, that helps to organize
computational problem solving communities and, more generally, constructive
formal scientific communities. We study the social choice theory of
side-choosing games, including appropriate axioms, a representation theorem
and a meritocracy theorem. While traditional social-choice theory studies
game-theoretic models of political institutions we study game-theoretic
models of formal scientific communities. Effective algorithmic solutions
are in high demand in numerous domains, such as big data, and we claim that
side-choosing games are an ideal tool to use Human Computation to find
effective algorithmic solutions.

Side-choosing games offer the benefit of fair, collusion-resistant peer
evaluation without a central authority, thereby lowering the effort of
organizing competitions similar to the ones held on TopCoder.com.
Side-choosing games are educational for players, giving them targeted
feedback on their choices and their defense. We report on our experience in
building computational problem solving communities in algorithm and
software development courses as a first application of our theory.
Joint Work with Ahmed Abdelmeged *(PhD Dissertation)
<http://www.ccs.neu.edu/home/lieber/theses/abdelmeged/scg/ahmed-thesis.html>
and Ruiyang Xu.*

*Speaker Bio:*

Karl Lieberherr is a Professor in the College of Computer and Information
Science at Northeastern University. He has contributed to Algorithms
(P-optimal Algorithms, Clause Learning for Satisfiability) and Modular
Software Design (Law of Demeter and several systems for Adaptive
Programming, a kind of Aspect-Oriented Programming). His latest interest is
in systems and their foundations for Human Computation for complex tasks,
e.g., algorithm development.

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