Authors’ final copy. Alex (with Andreas & Rob) got ABOD3 working on mobile phones so you can point your phone at a POSH / BOD robot and see what it’s trying to do. Software is probably available on github, just checking ...
Read MoreIncludes justification, motivation, strategies for systems engineering of AI, and strategies for regulating it. tl;dr see the bullet-point version in my blogpost, A smart bureaucrat’s guide to AI regulation.
Read MoreAnother nice piece of work on lightweight intelligent control and systems engineering of AI. Software is available online, like most software from my group.
Read MoreLike the title says, an attempt to simplify and improve on the systems for representing emotions and drives I wrote with Emmanuel Tanguy and Phil Rolphshagen (the Dynamic Emotion Representation (DER) and Flexible Latching respectively, see below).
Read MoreA summary of everything biology and biological anthropology have to say on the subject, for the benefit of roboticists in particular. Open access is as of late November 2014, a lightly updated version is now available in the Handbook.
Read MoreWhat’s visualised is the system’s priorities (the upper part of a POSH plan hierarchy), and which priorities are active in real time. Extends the IJCAI ethics workshop results to direct interaction with robots, and for an archival conference.
Read MoreIn honour of the EPSRC Principles of Robotics' fifth anniversary in 2016, Tony Prescott and Michael Szollosy ran an AISB symposium which was followed up by a special issue of the journal Connection Science the following year. Open access version.
Read MorePrecise manipulation (e.g. opening bottle caps) on real robots using social learning via contact sensors. Published online October 2015, in print June 2016. Open access available from authors, or Bath one day I hope.
Read MoreThe title references my earlier paper, A Role for Consciousness in Action Selection in the International Journal of Machine Consciousness 4(2):471-482, which I’m not sure is well enough known to take the confusion of the joke, but this paper has a fun model of selection for metacognition, mostly by Rob.
Read MoreAlso solving AI through social learning, this time game character strategies derived from human game traces. Open access camera ready version.
Read MoreA commentary on Social Behaviours in Dog-Owner Interactions Can Serve as a Model for Designing Social Robots in the same issue. Submitted version is open access.
Read MoreDescribes a system of biases for allowing machine learning by observation of sequences of behaviour. Final version from November 2013.
Read MoreDescribes Simon Davies’ undergraduate project on building strategic game AI, as extended using Swen Gaudl’s new version of ABODE.
Read MoreLike the title says. Work conducted at EPFL.
Read MoreAn invited chapter for a book written in honour of the late Brendan McGonigle. The chapter mostly takes a neuro and psychological approach, but last section is Eco Evo Devo, with some ideas I’ve been working on lately on the origins of cognition. This is the draft sent to the publisher in March 2010.
Read MoreDraft from January 2011.
Read MoreFinal version from March 2011.
Read MoreDiscusses a simple add-on mechanism for dynamic plans to allow sensible ordering of high-level drives, and explains why this problem is different from detailed action selection. Lots of experiments, some maths and some discussion of the literature on cognitive control in natural and artificial intelligence. Associated software comes with the standard python/jython distribution of BOD.
Read MorePenultimate draft, from May 2009. Related software and articles.
Read MoreThis is a somewhat pedantic overview of the improvements we’ve made to BOD, POSH and of course AI action selection in general in the last three years, with an eye to pleasing the EPSRC since my grant with the same title just ran out. Final version from January 2008.
Read MoreThat is actually just four pages, two of which introduce the articles. The first two pages though are an essay on the problem of action selection — it’s history & current status as a research problem. Written in December 2006.
Read MoreThis paper expands on the COIL system (presented first and more completely in the IEEE journal article) for imitation learning, showing how adding solid Bayesian representations improves both performance and extendibility. Final version from October 2006.
Read MoreThis paper presents an imitation learning system called COIL (inspired by Deb Roy’s CELL) capable of learning tasks in a dynamic real-time environment (Unreal Tournament). If you don’t subscribe to IEEE, here is a draft from May 2006. An even older version is Bath Technical report CSBU-2005-16.
Read MoreTalks about the work we and Prague have done on extending our BOD UT framework, kind of a “best of” summary paper from the games perspective. Final version from Nov 2006.
Read MoreDocuments BOD/MASON. It came out in 2006 because it took us a while to get everything working & written about (thanks Jan!). Version from July 2006.
Read MoreThis paper presents a Dynamic Emotion Representation (DER) model, its implementation and an instance of a full humanoid emotional model built with it. Penultimate draft version from May or June 2006. A longer version (which I think is more interesting though some terminology is wrong) is also a Bath technical report CSBU-2005-14, from November 2005
Read MoreA case study of using BOD, presents a very complicated POSH plan. Final version is copyright Springer. Updated 23 June 2005.
Read MoreShows that what picture is on a VR face has very significant impact on how the emotions are perceived. Final version is copyright Springer. Updated 23 June 2005
Read MoreFinal, 30 April 2004.
Read MoreThis is a longer, more detailed version of our IEEE Computer (2002) paper.
Read MoreJoanna Joy Bryson (postscript version). Warning: that version is 344 pages long, due to 140 pages of lisp code. I have broken the dissertation into its main text, code appendices and bibliography, (all in postscript), in the likely event you just want to read the text. You can also email me to ask for a copy of the printed Tech Report, which is paperback-like and doesn’t have the code. The files above are from the TR, which is clearer than the submitted dissertation (pdf). I also have had the Intelligence by Design Thesis Defense materials online since just after that 30 April 2001 defense.
Read MoreA brief document about Behavior Oriented Design (BOD). Slightly modified April 18, 2001.
Read MoreArticle concerns the design of constructive narratives. Describes SoL (a hybrid architecture composed of Edmund and Ymir), a slightly modified form of BOD to support SoL, and our experiences developing AI for constructive narratives at LEGO. Draft version from 18 Dec. 2000.
Read MoreTalks in detail about experimental method and the development of complex (even socially competent) agents. Updated July 2000.
Read MoreSummary: discusses the importance of methodology and the utility of alternative architectures — among other contributions, it distinguishes between these. Also gives a good one-page summary of what reactive planning really is. We suggest that the most useful thing to do with a new architecture is to identify its contributions and then express them in terms of one or more main-stream architectures. An extended example is made of an idiom we call a Basic Reactive Plan, taken from my architecture, Edmund, among other places. Updated 29 October 2000.
Read MoreSummary: demonstrates that hierarchy does not necessarily lead to a reduction of performance, even in highly dynamic environments. An illustration (with statistical evaluation) of the importance of clean design approaches to creating good AI systems. A shorter, less clear version of this paper appeared in Intelligent Virtual Agents 2, 1999. Final version; published in August 2000.
Read MoreSummary: article about trends in agent architectures and what they imply about optimal strategies for designing intelligence.
Read MoreLearning 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.
Read MoreThis 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)).
Read MoreDescribes 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).
Read MoreFor more information, see my page on the Reactive Accompanist (September 1992)
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