Cost-sensitive decision tree and cost-sensitive naïve Bayes are both new cost-sensitive learning models proposed recently to minimize the total cost of test and misclassifications...
The goal of this project is to develop an agent capable of learning and behaving autonomously and making decisions quickly in a dynamic environment. The agent’s environment is a...
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
Visually extracted 2D and 3D information have their own advantages and disadvantages that complement each other. Therefore, it is important to be able to switch between the differ...
Emre Baseski, Nicolas Pugeault, Sinan Kalkan, Dirk...
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...