We describe research on data-drive refinement and evaluation of a probabilistic model of student learning for an educational game on number factorization. The model is to be used b...
In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a a new probabilistic planning rule representation to compactly ...
Hanna M. Pasula, Luke S. Zettlemoyer, Leslie Pack ...
In this paper, we propose a comprehensive probabilistic framework which can be used to model and analyze cognitive radio (CR) network using carrier sensing (CS) based multiple acc...
We derive an asymptotic Newton algorithm for Quasi Maximum Likelihood estimation of the ICA mixture model, using the ordinary gradient and Hessian. The probabilistic mixture frame...
Jason A. Palmer, Scott Makeig, Kenneth Kreutz-Delg...
An urn-ball probabilistic model of the labor market is developed. Agents can be employed, (voluntary or involuntary) unemployed or entrepreneurs. The analytical long run equilibri...