For agents and robots to become more useful, they must be able to quickly learn from non-technical users. This paper investigates the problem of interactively learning behaviors communicated by a human teacher using positive and negative feedback. Much previous work on this problem has made the assumption that people provide feedback for decisions that is dependent on the behavior they are teaching and is independent from the learner's current policy. We present empirical results that show this assumption to be false---whether human trainers give a positive or negative feedback for a decision is influenced by the learner's current policy. We argue that policy-dependent feedback, in addition to being commonplace, enables useful training stra...
The ability to adapt and learn can help robots deployed in dynamic and varied environments. While in...
Reactions such as gestures and facial expressions are an abundant, natural source of signal emitted ...
textRobots and other computational agents are increasingly becoming part of our daily lives. They wi...
Abstract — In order to be useful in real-world situations, it is critical to allow non-technical use...
A long term goal of Interactive Reinforcement Learning is to incorporate non-expert human feedback t...
Thesis (Ph.D.), Computer Science, Washington State UniversityAs the number of deployed robots grows,...
As robots become a mass consumer product, they will need to learn new skills by interacting with typ...
AbstractWhile Reinforcement Learning (RL) is not traditionally designed for interactive supervisory ...
In this work, we address a relatively unexplored aspect of designing agents that learn from human re...
This paper introduces two novel algorithms for learning behaviors from human-provided rewards. The p...
University of Technology Sydney. Faculty of Engineering and Information Technology.A promising metho...
Keeping a human in a robot learning cycle can provide many advantages to improve the learning proces...
designed for interactive supervisory input from a human teacher, several works in both robot and sof...
Copyright© (2013) by Neural Information Processing SystemsPresented at the 27th Annual Conference on...
rithm enables a human user to train a robot by providing rewards in response to past actions and ant...
The ability to adapt and learn can help robots deployed in dynamic and varied environments. While in...
Reactions such as gestures and facial expressions are an abundant, natural source of signal emitted ...
textRobots and other computational agents are increasingly becoming part of our daily lives. They wi...
Abstract — In order to be useful in real-world situations, it is critical to allow non-technical use...
A long term goal of Interactive Reinforcement Learning is to incorporate non-expert human feedback t...
Thesis (Ph.D.), Computer Science, Washington State UniversityAs the number of deployed robots grows,...
As robots become a mass consumer product, they will need to learn new skills by interacting with typ...
AbstractWhile Reinforcement Learning (RL) is not traditionally designed for interactive supervisory ...
In this work, we address a relatively unexplored aspect of designing agents that learn from human re...
This paper introduces two novel algorithms for learning behaviors from human-provided rewards. The p...
University of Technology Sydney. Faculty of Engineering and Information Technology.A promising metho...
Keeping a human in a robot learning cycle can provide many advantages to improve the learning proces...
designed for interactive supervisory input from a human teacher, several works in both robot and sof...
Copyright© (2013) by Neural Information Processing SystemsPresented at the 27th Annual Conference on...
rithm enables a human user to train a robot by providing rewards in response to past actions and ant...
The ability to adapt and learn can help robots deployed in dynamic and varied environments. While in...
Reactions such as gestures and facial expressions are an abundant, natural source of signal emitted ...
textRobots and other computational agents are increasingly becoming part of our daily lives. They wi...