Tournament Decision Theory

A Tournament of Party Decision Rules

Following Axelrod's tournaments for strategies in the repeat-play prisoner's dilemma, we ran a ''tournament of party decision rules'' in a dynamic agent-based model of party competition. We asked researchers to submit rules for selecting party positions in a two-dimensional policy space, pitting each rule against all others in a suite of long-running simulations. The most successful rule combin...

A theory of knockout tournament seedings

This paper provides nested sets and vector representations of knockout tournaments. The paper introduces classification of probability domain assumptions and a new set of axioms. Two new seeding methods are proposed: equal gap seeding and increasing competitive intensity seeding. Under different probability domain assumptions, several axiomatic justifications are obtained for equal gap seeding....

Tournament Solutions and Their Applications to Multiagent Decision Making

Applying Cognitive Architectures to Decision-Making: How Cognitive Theory and the Equivalence Measure Triumphed in the Technion Prediction Tournament

For the Technion Prediction Tournament, we developed a model of making repeated binary choices between a safe option and a risky option. The model is based on the ACT-R declarative memory system, with the use of the Blending mechanism and sequential dependencies. By using established cognitive theory, rather than specialized machine learning techniques, our model was the most predictive when ge...

Decision Theory

Decision theory seeks to establish general principles of rationality to guide decision makers in situations involving risk or uncertainty. It is a vibrant subject covering many academic disciplines with numerous subspecialties. I cannot hope to do justice to even a small portion of the recent developments in a piece of this length, so I will confine my attention to what I see as the threl most ...