Modeling expert problem solving in a game of chance: a Yahtzee© case study
Ken Maynard, Patrick Moss, Marcus Whitehead, Srinidhi Narayanan, Matt Garay, Nathan G. Brannon, Raj Gopal Prasad Kantamneni, Todd Kustra · Expert Systems · 2001
Although developments on software agents have led to useful applications in automation of routine tasks such as electronic mail filtering, there is a scarcity of research that empirically evaluates the performance of a software agent versus that of a human reasoner, whose problem‐solving capabilities the agent embodies. In the context of a game of a chance, namely Yahtzee©, we identified strategies deployed by expert human reasoners and developed a decision tree for agent development. This paper describes the computer implementation of the Yahtzee game as well as the software agent. It also presents a comparison of the performance of humans versus an automated agent. Results indicate that, in this context, the software agent embodies human expertise at a high level of fidelity.