Online auctions have become extremely popular in recent years. Ability to predict winning bid prices accurately can help bidders to maximize their profit. This paper proposes a nu...
We build the generic methodology based on machine learning and reasoning to detect the patterns of interaction between conflicting agents, including humans and their assistants. L...
In addressing the challenge of exponential scaling with the number of agents we adopt a cluster-based representation to approximately solve asymmetric games of very many players. ...
This research describes a probabilistic approach for developing predictive models of how students learn problem-solving skills in general qualitative chemistry. The goal is to use ...
Ron Stevens, Amy Soller, Melanie Cooper, Marcia Sp...
Abstract- We present a concept for developing cooperative characters (agents) for computer games that combines coaching by a human with evolutionary learning. The basic idea is to ...