There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
Forecasting future events based on historic data is useful in many domains like system management, adaptive query processing, environmental monitoring, and financial planning. We...
This paper describes a new model for understanding natural language commands given to autonomous systems that perform navigation and mobile manipulation in semi-structured environ...
Stefanie Tellex, Thomas Kollar, Steven Dickerson, ...
This paper presents an agent-based approach to assisting learners to dynamically adjust learning processes. The online learning process is first investigated where the importance ...
We present a logical approach to plan recognition that builds on Kautz's theory of keyhole plan recognition, defined as the problem of inferring descriptions of high-level pl...