Quite a bit is known about minimizing different kinds of regret in experts problems, and how these regret types relate to types of equilibria in the multiagent setting of repeated...
We present a general methodology to automate the search for equilibrium strategies in games derived from computational experimentation. Our approach interleaves empirical game-the...
This paper demonstrates the applicability of reinforcement learning for first person shooter bot artificial intelligence. Reinforcement learning is a machine learning technique wh...
Providing compelling, realistic, immersive game worlds is one of the major goals in modern game design. The presence of unique and interesting dialogue for all of the characters i...
We discuss the design of the Intermediary Agent's brain, the control module of an embodied conversational virtual peer in a simulation game aimed at providing learning experi...