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Interactive Machine Learning

MAS.S62 Interactive Machine Learning (0-12-0), H-Level Fall 2013 Instructor: Dr. Brad Knox (principal), with Prof. Cynthia Breazeal (and early critical help

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Interactive Machine Learning | iml.media.mit.edu Reviews
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Interactive Machine Learning | iml.media.mit.edu Reviews

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MAS.S62 Interactive Machine Learning (0-12-0), H-Level Fall 2013 Instructor: Dr. Brad Knox (principal), with Prof. Cynthia Breazeal (and early critical help

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Ideas For Dozens

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Compelling vs Compulsive Games: Threes, Super Hexagon, and The Replay Urge. February 19, 2014. Note: As part of an independent study this semester at the MIT Media Lab on game design, I’ve begun blogging about games here: playedgame.tumblr.com. I’ll ocassionally cross-post more developed pieces like this one, but feel free to follow that Tumblr if you’d to read more of my writing about games. Compelling games reward you for repeated play, investing the time they extract from you into a deepening experien...

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Bio | W Bradley Knox, PhD

http://www.bradknox.net/front-page/bio

W Bradley Knox, PhD. Train a TAMER agent. Brad Knox is founder and CEO of Emoters. Brad Knox is founder and CEO of Emoters. W Bradley Knox, PhD. Middot; Machine learners, human teachers. Robots optional. Proudly powered by WordPress. Middot; Theme: Pilcrow by Automattic.

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TAMER in Action | W Bradley Knox, PhD

http://www.bradknox.net/human-reward/tamer/tamer-in-action

W Bradley Knox, PhD. Train a TAMER agent. Videos of TAMER agents before, during, and after training:. W Bradley Knox, PhD. Middot; Machine learners, human teachers. Robots optional. Proudly powered by WordPress. Middot; Theme: Pilcrow by Automattic.

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Human Reward | W Bradley Knox, PhD

http://www.bradknox.net/human-reward

W Bradley Knox, PhD. Train a TAMER agent. Much of my research has focused roughly on the question: If reward in a reinforcement learning framework is given by a live human trainer. As he or she observes the agent’s behavior rather than from the usual pre-coded reward function how should an agent use these feedback signals to best learn the behavior that the human intends to teach? Below are links to explore my work with Peter Stone and others on learning from human reward. W Bradley Knox, PhD.

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Blog | W Bradley Knox, PhD | Machine learners, human teachers. Robots optional.

http://www.bradknox.net/blog

W Bradley Knox, PhD. Train a TAMER agent. 2014/05/07 · 10:39 pm. Personal Robots Group at MIT is recruiting kids and parents for a study! The Personal Robots Group at the MIT Media Lab is looking for participants for a research study and is offering an opportunity for you and your children to visit with one of our robots in our lab! If you are interested in participating, please select a time slot at this link:. Simply direct your referral to the sign-up link at mitrobots.youcanbook.me. What is a robot?

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Non-Myopic Learning | W Bradley Knox, PhD

http://www.bradknox.net/human-reward/learning-non-myopically

W Bradley Knox, PhD. Train a TAMER agent. Acknowledging that the agent’s learning objective (e.g., maximize immediate reward or sum of reward over the long-term) may or may not line up with performance on the trainer’s intended task (e.g., follow the human trainer), we examined the relationships between reward positivity, temporal discounting, episodicity, and task performance. Contributions of this work include. The first successful instance of non-myopic learning from human reward. Learning Non-Myopica...

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Learning from Human-Generated Reward | W Bradley Knox, PhD

http://www.bradknox.net/dissertation

W Bradley Knox, PhD. Train a TAMER agent. Learning from Human-Generated Reward. How and to what extent can agents harness the information contained in human-generated signals of reward to learn sequential decision-making tasks? W Bradley Knox, PhD. Middot; Machine learners, human teachers. Robots optional. Proudly powered by WordPress. Middot; Theme: Pilcrow by Automattic.

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Download TAMER | W Bradley Knox, PhD

http://www.bradknox.net/human-reward/tamer/download-tamer-codebase

W Bradley Knox, PhD. Train a TAMER agent. When I can grab some spare time, I’m inching towards making the TAMER codebase available, along with related goodies like an applet interface for running experiments through people’s browsers and some implementations of basic RL and learning from demonstration algorithms. For now though, an unofficial release can be found at https:/ github.com/bradknox/tamerproject/. Specifically, follow these instructions to get the project working for now. W Bradley Knox, PhD.

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Train a TAMER agent | W Bradley Knox, PhD

http://www.bradknox.net/human-reward/tamer/train-a-tamer-agent

W Bradley Knox, PhD. Train a TAMER agent. Train a TAMER agent. If you’re interested, feel free to email me to request that I put the training applets up, which let you try out training an agent through positive and negative feedback. W Bradley Knox, PhD. Middot; Machine learners, human teachers. Robots optional. Proudly powered by WordPress. Middot; Theme: Pilcrow by Automattic.

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Interactive Machine Learning

MASS62 at the MIT Media Lab. MASS62 Interactive Machine Learning (0-12-0), H-Level. Instructor: Dr. Brad Knox. Principal), with Prof. Cynthia Breazeal. And early critical help from Dr. Nick Gillian. Samples of student work. Thanks to all of my fantastic students and our inspiring guest speakers this semester. Some of these students created videos of their work, a few of which I share below. A more formal description of the course is below the videos. The course will consist of small hands-on projects and...

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