We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
Following verbal route instructions requires knowledge of language, space, action and perception. We present MARCO, an agent that follows free-form, natural language route instruc...
Matt MacMahon, Brian Stankiewicz, Benjamin Kuipers
Appeared in: P. Bouquet, P. Br´ezillon, L. Serafini, M. Benerecetti, F. Castellani (Eds.), 2nd International and Interdisciplinary Conference on Modeling and Using Context (CONT...
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
We present a system that learns to follow navigational natural language directions. Where traditional models learn from linguistic annotation or word distributions, our approach i...