Rating computer science via chess in memoriam daniel kopec and hans berliner

Abstract

Computer chess was originally purposed for insight into the human mind. It became a quest to get the most power out of computer hardware and software. The goal was specialized but the advances spanned multiple areas, from heuristic search to massive parallelism. Success was measured not by standard software or hardware benchmarks, nor theoretical aims like improving the exponents of algorithms, but by victory over the best human players. To gear up for limited human challenge opportunities, designers of chess machines needed to forecast their skill on the human rating scale. Our thesis is that this challenge led to ways of rating computers on the whole and also rating the effectiveness of our field at solving hard problems. We describe rating systems, the workings of chess programs, advances from computer science, the history of some prominent machines and programs, and ways of rating them.