Modeling expert problem solving in a game of chance: a Yahtzee (c) case study

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 softwa re agent versus that of a human reasoner, whose problem-solving capabilitie s the agent embodies. In the context of a game of a chance, namely Yahtzee( C), we identified strategies deployed by expert human reasoners and develop ed 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 agen t. Results indicate that, in this context, the software agent embodies huma n expertise at a high level of fidelity.