TY - GEN
T1 - Performance and prediction
T2 - 12th International Conference on Advances in Computer Games, ACG 2009
AU - Haworth, Guy
AU - Regan, Ken
AU - Di Fatta, Giuseppe
PY - 2010
Y1 - 2010
N2 - Evaluating agents in decision-making applications requires assessing their skill and predicting their behaviour. Both are well developed in Poker-like situations, but less so in more complex game and model domains. This paper addresses both tasks by using Bayesian inference in a benchmark space of reference agents. The concepts are explained and demonstrated using the game of chess but the model applies generically to any domain with quantifiable options and fallible choice. Demonstration applications address questions frequently asked by the chess community regarding the stability of the rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The last include alleged under-performance, fabrication of tournament results, and clandestine use of computer advice during competition. Beyond the model world of games, the aim is to improve fallible human performance in complex, high-value tasks.
AB - Evaluating agents in decision-making applications requires assessing their skill and predicting their behaviour. Both are well developed in Poker-like situations, but less so in more complex game and model domains. This paper addresses both tasks by using Bayesian inference in a benchmark space of reference agents. The concepts are explained and demonstrated using the game of chess but the model applies generically to any domain with quantifiable options and fallible choice. Demonstration applications address questions frequently asked by the chess community regarding the stability of the rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The last include alleged under-performance, fabrication of tournament results, and clandestine use of computer advice during competition. Beyond the model world of games, the aim is to improve fallible human performance in complex, high-value tasks.
UR - https://www.scopus.com/pages/publications/77953794054
U2 - 10.1007/978-3-642-12993-3_10
DO - 10.1007/978-3-642-12993-3_10
M3 - Conference contribution
AN - SCOPUS:77953794054
SN - 3642129927
SN - 9783642129926
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 99
EP - 110
BT - Advances in Computer Games - 12th International Conference, ACG 2009, Revised Papers
Y2 - 11 May 2009 through 13 May 2009
ER -