This paper develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans. PHA...
This paper introduces a HMM-based speech synthesis system which uses a new method for the Separation of Vocal-tract and LiljencrantsFant model plus Noise (SVLN). The glottal sourc...
Most real-world negotiation scenarios involve multiple, interdependent issues. These scenarios are specially challenging because the agents' utility functions are nonlinear, ...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
— In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do t...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...