The Design of Learning for an Artifact
Joanna Bryson, from the AISB96 workshop on Learning in Robots and Animals. (There's also an older, longer version about Cog.)
Learning in animals seems to be highly specialized and constrained as much as possible, primarily to things that cannot be learned in evolutionary time scales. As developers of behavior-based AI, we largely take on the role of evolutionary learning ourselves. Our robots or avatars should only have the special-purpose sorts of learning built-in to their everyday actions.
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Modular Adaptivity and Behavior Based Control [Draft]
Joanna Bryson, 1996.
A short paper which discusses the role of episodic memory in navigation. I got some of this working on my robot, see my MPhil thesis, but some of it still needs to get worked out and written up ...
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Primitive Parallax and Parallax Primitives (pdf) [Draft]
Joanna Bryson, 1995.
My only machine vision paper (so far), written in the context of MIT’s (Rod Brooks & Lynn Andrea Stein’s) Cog project. In late 1994, still basically the only thing that worked on the robot was its cameras, and I needed to do some research (and get the thing closer to being a person) so I used those. This was submitted to the European Conference on Artificial Life, and accepted but only as a poster with a brief abstract. In 2024 I found this PDF on an Internet research paper archive; I have no idea how it got there.
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The Use of State in Intelligent Control [Draft]
Joanna Bryson, 1995.
This short paper compares Shakey and Genghis, and demonstrates the necessity of using control state even in the simplest reactive system. I’m not sure anyone cares enough for me to ever get this one published! But I still think it could be useful for some people. (The original Genghis didn’t actually back up and turn when it bumped into something with a feeler. It just lifted its leg higher. Ooops. Oh well, the same arguments still all apply. The behavior I described was on the commercial version of Genghis available then from ISR (now iRobot)).
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The Reactive Accompanist: Adaptation and Behavior Decomposition in a Music System
Joanna Bryson, in Luc Steels (ed.) The Biology and Technology of Intelligent Autonomous Agents, 1994.
Describes my MSc project, is also the first place I suggest adaptive requirements can serve as a key to determining how to decompose intelligence into modularized behaviors (key point in BOD).
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The Reactive Accompanist: Applying Subsumption Architecture to Software Design
Edinburgh University Department of AI tech report 606, 1992.
This paper is temporarily (January 2003) inaccessible due to the Edinburgh fire. Since ‘temporary’ has lasted for over two years, here’s a draft version I still had the latex for. Compares Subsumption Architecture with Object-Oriented Design in the context of my MSc. Draft was last modified around November 1992, it was placed here March 2005.
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The Subsumption Strategy Development of a Music Modelling System
MSc Dissertation, University of Edinburgh, Faculty of Science (Department of Artificial Intelligence), 1992.
For more information, see my page on the Reactive Accompanist (September 1992)
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