SCG Court: A Crowdsourcing Platform for Computational Problems

Speaker: Karl Lieberherr, College of Computer and Information Science, PRL, Northeastern University, Boston, Massachusetts.

When: Thursday July 7, 2011, 11.00

Where: ETH Zurich, RZ F 21


A recent Communication of the ACM article on Crowdsourcing Systems (April 2011) points to the importance of crowdsourcing platforms to simplify the development of crowdsourcing systems. We present the Scientific Community Game Court (SCG Court) a crowdsourcing platform (a web application) parameterized by a playground X and our experience in using it for driving innovation in several domains.

The Scientific Community Game involves proposing and opposing claims related to a constructive domain (e.g., domains in computer science, mathematics, engineering, etc.). Central to opposing claims is refuting claims based on a refutation protocol. When playing the game, players make constructive claims about the domain and oppose others' claims. The players who are the most successful in defending and opposing claims win the game and gain a high reputation in the community. Adopting an SCG-centric research process has the following benefits:
(1) it focuses researchers on a specific domain by defining a language for expressing claims about that domain. Thus, reducing the amount of management effort. The numerous contributions from the crowd of researchers are effectively combined by the game to build a knowledge base through voting with justification. The game is egalitarian and the production of software is social without a central human authority (committers).
(2) it provides a structured framework for collaboration between researchers. The researchers provide and receive frequent feedback on their claims from their peers. Players who lose points gain knowledge to improve their game in the future. This makes collaboration more effective.
(3) it accumulates knowledge in playground X. The game produces both a knowledge base (the social welfare coming from the game) as well as useful know-how to defend the claims in the knowledge base. For some playgrounds, the know-how consists of a clever algorithm, if the domain is well understood. For other playgrounds that are less understood, the know-how is heuristic.
(4) researchers are motivated towards proposing and opposing non-trivial claims in order to gain reputation. They like to win and if they lose, they want to find out why.
(5) managers get a fair comparison of the skills of their researchers through the competition results.
(6) controlled teaching and learning through the game. Researchers who introduce new knowledge entice other researchers to assimilate the same or better knowledge. Researchers that don't participate in this activity, lose reputation, as they would in a real scientific community. The game is fun and adjusts to the skill levels of players.

The SCG can be played productively for: (1) developing reliable software for computational problems, (2) evaluating potential employees, (3) developing new knowledge in the given domain, (4) evaluating algorithmic innovations fairly, and (5) teaching software development / problem solving techniques in a fun game environment.

More information on SCG is available from: SCG Home Page.

Supported by Novartis. Joint work with Ahmed Abdelmeged.

Short Speaker Bio

Karl Lieberherr started his research career in computer science as a theoretical computer scientist, focusing on the theory of P-optimal algorithms for the generalized maximum satisfiability problem (MAX-CSP), still an active area of research. This work has motivated the development of a game platform for refutation-based, constructive scientific domains, called the Scientific Community Game (SCG) also known as the Specker Challenge Game, named after ETH Professor Emeritus Ernst Specker. He also invented, independently and simultaneously on the other side of the Atlantic (at ETH Zurich), an early form of non-chronological backtracking based on learned clauses (superresolution) which has become a key feature of most state-of-the-art SAT and CSP solvers.

In the mid 1980s, he switched to his current research area: Object-Oriented and Aspect-Oriented Software Development and focused on issues of software design and modularity. He founded the Demeter research team, which studied the then-novel idea of Adaptive Programming, also known as structure-shy programming and produced the Law of Demeter ("talk only to your friends": an explicit form of coupling control) and several systems for separating concerns in an object-oriented programming context: From Demeter/Flavors to DemeterF. DemeterF is used in the implementation of SCG.

Dr. Lieberherr is a Professor in the College of Computer and Information Science at Northeastern University.