Spartan Daily, February 14, 1939

Volume 27, Issue 84https://scholarworks.sjsu.edu/spartandaily/2874/thumbnail.jp

The Sport League's Dilemma: Competitive Balance versus Incentives to Win

We analyze a dynamic model of strategic interaction between a professional sport league that organizes a tournament, the teams competing to win it, and the broadcasters paying for the rights to televise it.Teams and broadcasters maximize expected profits, while the league's objective may be either to maximize the demand for the sport or to maximize the teams'joint profits.Demand depends positively on symmetry among teams (competitive balance) and how aggressively teams try to win (incentives to win).Revenue sharing increases competitive balance but decreases incentives to win.Under demand maximization, a performance-based reward scheme (used by European sport leagues) may be optimal. Under joint profit maximization, full revenue sharing (used by many US leagues) is always optimal.These results reflect institutional differences among European and American sports leagues.sport;competition;incentives;broadcasting industry;revenue sharing

Evolutionary Artificial Neural Network Weight Tuning to Optimize Decision Making for an Abstract Game

Abstract strategy games present a deterministic perfect information environment with which to test the strategic capabilities of artificial intelligence systems. With no unknowns or random elements, only the competitors’ performances impact the results. This thesis takes one such game, Lines of Action, and attempts to develop a competitive heuristic. Due to the complexity of Lines of Action, artificial neural networks are utilized to model the relative values of board states. An application, pLoGANN (Parallel Lines of Action with Genetic Algorithm and Neural Networks), is developed to train the weights of this neural network by implementing a genetic algorithm over a distributed environment. While pLoGANN proved to be designed efficiently, it failed to produce a competitive Lines of Action player, shedding light on the difficulty of developing a neural network to model such a large and complex solution space

Spartan Daily, March 28, 1984

Volume 82, Issue 41https://scholarworks.sjsu.edu/spartandaily/7159/thumbnail.jp

Spartan Daily, December 4, 1984

Volume 83, Issue 62https://scholarworks.sjsu.edu/spartandaily/7248/thumbnail.jp

The BG News November 5, 1997

The BGSU campus student newspaper November 5, 1997. Volume 80 - Issue 50https://scholarworks.bgsu.edu/bg-news/7240/thumbnail.jp

Spartan Daily, January 23, 1998

Volume 110, Issue 2https://scholarworks.sjsu.edu/spartandaily/9218/thumbnail.jp

1979 July-December

Morehead State Athletics press releases from July to December of 1979