With the aim of fluency and efficiency in human-robot teams, we have developed a cognitive architecture based on the neuro-psychological principles of anticipation and perceptual ...
We describe HTN-MAKER, an algorithm for learning hierarchical planning knowledge in the form of decomposition methods for Hierarchical Task Networks (HTNs). HTNMAKER takes as inpu...
Checking CSP consistency is shown, in theory, to be an NP-complete problem. There is two families of methods for CSP consistency checking. The first family holds the complete meth...
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...