153 citations · 385 across the 25 of their papers we have counts for
10 papers · 1 filter
Leveraging Human Guidance for Deep Reinforcement Learning Tasks
Ruohan Zhang, Faraz Torabi, Lin Guan +2
Reinforcement learning agents can learn to solve sequential decision tasks by interacting with the environment. Human knowledge of how to solve these tasks can be incorporated usin…
Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report
Rishi Shah, Yuqian Jiang, Haresh Karnan +8
RoboCup@Home is an international robotics competition based on domestic tasks requiring autonomous capabilities pertaining to a large variety of AI technologies. Research challenge…
Unclogging Our Arteries: Using Human-Inspired Signals to Disambiguate Navigational Intentions
Justin Hart, Reuth Mirsky, Stone Tejeda +5
People are proficient at communicating their intentions in order to avoid conflicts when navigating in narrow, crowded environments. In many situations mobile robots lack both the…
Desiderata for Planning Systems in General-Purpose Service Robots
Nick Walker, Yuqian Jiang, Maya Cakmak +1
General-purpose service robots are expected to undertake a broad range of tasks at the request of users. Knowledge representation and planning systems are essential to flexible aut…
Reasoning about Hypothetical Agent Behaviours and their Parameters
Stefano V. Albrecht, Peter Stone
Agents can achieve effective interaction with previously unknown other agents by maintaining beliefs over a set of hypothetical behaviours, or types, that these agents may have. A…
Recent Advances in Imitation Learning from Observation
Faraz Torabi, Garrett Warnell, Peter Stone
Imitation learning is the process by which one agent tries to learn how to perform a certain task using information generated by another, often more-expert agent performing that sa…