Posts tagged Systems Engineering
Effects of Transparency in Humanoid Robots - A Pilot Study

Heinrich Mellmann, Polina Arbuzova, Dimosthenis Kontogiorgos, Magdalena Yordanova, Jennifer X. Haensel, Verena V. Hafner, and Joanna J. Bryson, HRI '24: Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 750-754, 11 March 2024.

Transparency is recognized as a vital feature for understanding and predicting robot behavior. Another feature that affects interaction with robots is their anthropomorphism. The relationship between these remains under-explored but is postulated to be negative. We present a pilot study investigating the effects of robot transparency in human-robot interactions, where the robot has an anthropomorphic appearance. We asked participants to evaluate and interact with the humanoid robot Pepper to examine whether visualizing the robot’s goals and behavior affects perceived intelligence, anthropomorphism, and robot agency. Our preliminary findings suggest that users may attribute higher ratings of agency when interacting with a robot visualizing its goals. In this late-breaking report, we propose our experiment on the interplay between transparency and anthropomorphism in human-robot interaction and summarize insights from our preliminary pilot study.

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Improving Robot Transparency: An Investigation With Mobile Augmented Reality (pdf)

Alexandros Rotsidis, Andreas Theodorou, Joanna J. Bryson, and Robert H. Wortham, to be presented at RO-MAN 2019.

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 ...

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How Society Can Maintain Human-Centric Artificial Intelligence (pdf)

Joanna J. Bryson and Andreas Theodorou, solicited and reviewed chapter (title given) in the collection Human-Centered Digitalization and Services, Marja Toivonen-Noroand Eveliina Saari (eds.), Springer, 2019.

Includes 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.

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The Extended Ramp Model: A Biomimetic Model of Behaviour Arbitration for Lightweight Cognitive Architectures

Swen E. Gaudl and Joanna J. Bryson, Cognitive Systems Research, 50:1-9 (this journal seems to count issues as volumes), 2018.

Like 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).

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Communication (pdf)

Rob Wortham and Joanna J. Bryson, open access version, in Living Machines: A Handbook of Research in Biomimetic and Biohybrid Systems, Prescott and Verschure, eds, Oxford University Press, 2018.

A 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.

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Improving Robot Transparency: Real-Time Visualisation of Robot AI Substantially Improves Understanding in Naive Observers

Robert H Wortham, Andreas Theodorou, Joanna J Bryson, in The 26th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2017.

What’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.

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Designing and Implementing Transparency for Real Time Inspection of Autonomous Robots

Andreas Theodorou, Rob Wortham, and Joanna J. Bryson, Connection Science, 29(3):230-241, 2017.

In 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.

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A Role for Action Selection in Consciousness: An Investigation of a Second-Order Darwinian Mind

Robert H. Wortham and Joanna J. Bryson, in the CEUR Workshop Proceedings, published December 2016.

The 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.

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Learning from Play: Facilitating Character Design Through Genetic Programming and Human Mimicry

Swen E. Gaudl, Joseph Carter Osborn, and Joanna J. Bryson, from Progress in Artificial Intelligence: Proceedings of 17th Portuguese Conference on Artificial Intelligence, EPIA 2015, Coimbra, Portugal, September 8-11, 2015.

Also solving AI through social learning, this time game character strategies derived from human game traces. Open access camera ready version.

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Structuring Intelligence: The Role of Hierarchy, Modularity and Learning in Generating Intelligent Behaviour (pdf)

Joanna J. Bryson, from McFarland, D., Stenning, K. and McGonigle-Chalmers, M. (eds.) The Complex Mind, on Palgrave MacMillan, 2012.

An 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.

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Flexible Latching: A Biologically-Inspired Mechanism for Improving the Management of Homeostatic Goals

Philipp Rohlfshagen and Joanna J. Bryson, Cognitive Computation, 2(3):230-241, 2010.

Discusses 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.

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The Impact of Durative State on Action Selection (pdf)

Joanna J. Bryson, appeared in Emotion, Personality, and Social Behavior at the AAAI 2008 Spring Symposia at Stanford in March.

This 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.

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Representations for Action Selection Learning from Real-Time Observation of Task Experts (pdf)

Mark Wood and Joanna J. Bryson, in IJCAI 2007, presented in Hyderabad in January 2007.

This 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.

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Skill Acquisition Through Program-Level Imitation in a Real-Time Domain

Mark Wood and Joanna J. Bryson, IEEE Transactions on Systems Man and Cybernetics, 37(2):272-285, 2007.

This 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.

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A Dynamic Emotion Representation Model Within a Facial Animation System (pdf)

Emmanuel A. R. Tanguy, Phil J. Willis, and Joanna J. Bryson, The International Journal of Humanoid Robotics, 3(3):293-300., 2006

This 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

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Intelligence by Design (pdf)

PhD Dissertation: Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2001.

Joanna 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.

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Dragons, Bats & Evil Knights: A Three-Layer Design Approach to Character Based Creative Play

Joanna Bryson and Kris Thórisson. Final version appeared in Virtual Reality, 5(2):57-71, a special issue on Intelligent Virtual Agents edited by Daniel Ballin, 2000.

Article 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.

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Architectures and Idioms: Making Progress in Agent Design (pdf)

Joanna Bryson and Lynn Andrea Stein (postscript), presented at ATAL 2000, now a book chapter, the final version is © Springer-Verlag, 2000.

Summary: 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.

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Hierarchy and Sequence vs. Full Parallelism in Reactive Action Selection Architectures

Joanna Bryson, in The Sixth International Conference on the Simulation of Adaptive Behavior (SAB2000) (Note: there’s a pdf version with an extra blank page.)

Summary: 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.

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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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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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