Many non-cooperative settings that could potentially be studied using game theory are characterized by having very large strategy spaces and payoffs that are costly to compute. Be...
—We examine the use of teleological metareasoning for self-adaptation in game-playing software agents. The goal of our work is to develop an interactive environment in which the ...
Joshua Jones, Chris Parnin, Avik Sinharoy, Spencer...
A key problem in playing strategy games is learning how to allocate resources effectively. This can be a difficult task for machine learning when the connections between actions a...
Abstract. In this work, we describe the process used in order to predict the bidding strategy of trading agents. This was done in the context of the Reverse TAC, or CAT, game of th...
The intrinsic motivation to play, and therefore to learn, that might be provided by digital educational games teases researchers and developers. However, existing educational games...
Michael D. Kickmeier-Rust, Neil Peirce, Owen Conla...