Abstract--Acquisition of new sensorimotor knowledge by imitation is a promising paradigm for robot learning. To be effective, action learning should not be limited to direct replic...
This work addresses the problem of efficiently learning action schemas using a bounded number of samples (interactions with the environment). We consider schemas in two languages-...
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential structure of a model selection ...
We have been developing Rogue, an architecture that integrates high-level planning with a low-level executing robotic agent. Rogue is designed as the oce gofer task planner for X...
People interact with interfaces to accomplish goals, and knowledge about human goals can be useful for building intelligent user interfaces. We suggest that modeling high, human-l...