Effective algorithmic solutions are in high demand in numerous domains, such as big data. Algorithm competitions are productive systems to push the state-of-the-art of solving a computational problem. TopCoder and similar platforms are prominent examples. Our competition design is effective from two viewpoints. (1) We minimize the effort on the competition administration by distributing the work of evaluation among participants while guaranteeing a fair evaluation. (2) We minimize the effect of collusion so that the strong participants cannot be outnumbered by colluding participants. Our design is axiomatic in that we formulate axioms (including a collusion-resistant axiom) for ranking functions and we prove a representation theorem. It shows that all ranking functions satisfying the axioms must have an elegant property useful for collusion-resistant mechanism design. Our competition design approach introduces a new class of games, called side-choosing games, and advances our knowledge about semantic games, a well-studied area in logic.
In addition to algorithm competitions, our system and its theoretical foundation is also useful to pushing the state-of-the-art in formal sciences and in education in formal sciences. Indeed, the system was developed in the context of education (Algorithms and Software Development Courses) to facilitate fair peer grading and focused communication among students. Our system is also a model of a Popperian scientific community where claims are being made, attacked and refuted. The educational benefits of side-choosing games have a direct implication for the crowd workers: They get valuable feedback when they lose.