Emmet Spier. Room 5C13 x3594. emmet@cogs.sussex.ac.uk
Course outline [pdf]
Online Course Library collection of digitally available course readings
Assessed Essay Details and Tips
An introductory lecture (Adrian Thompson) [link]
Reading
Brooks, R (1991) Artificial life and Real Robots, Proceedings of ECAL91, 3-10.
A short overview, available from the course library
Jakobi, N (1998) Evolutionary Robotics and the Radical Envelope of Noise Hypothesis, Adaptive Behavior, 6(2), 326-368.
A detailed example, available from the course library
Webb, B (in press) Can Robots Make Good Models of Biological Behaviour? Behavioural Brain Sciences
A long, less active, overview
Reading
Available from Celia McInnes in the COGS library
Grey Walter (1950) An Imitation of Life, Scientific American, 182(5).
Grey Walter (1951) A Machine That Learns, Scientific American, 185(2).
Pask, Gordon (1962) A Proposed Evolutionary Model. In `Principles of Self-
Organization', Von Foerster and Zopf (Eds), 299-253, Permagon Press.
-- Last year I convinced myself that the Pask paper was a cellular automata model similar to Conway's
game of life. Is this believable given his details?
Some (old) links
Grey Walter's robots
rebuilt
Reference to Owen Holland paper about Grey
Walter and the robot rebuild.
Gordon Pask information.
From Complexity to
Perplexity on-line version of Sci. Am. critique of `The Science of
Complexity' (original magazine article is longer)
Randall Beer Proponent of the
dynamical systems approach. See "On the dynamics of small continuous-time
recurrent neural networks" cf. Grey Walter's "two neurons"
MS Windows simulation of Walter's
tortoises.
More tortoise
stuff.
* Fungus Eaters' Seminar
Pfeifer (1996) Building "Fungus Eaters": Design principles of autonomous agents. SAB98 pp 3-12 (in on-line library)
Q: Can the principles be ranked in terms of their importance for building robots? What is/are the most fundamental for adaptive behaviour?
Stein and Meredith (1993) The merging of the senses. Ch.2. QU 4590ste. (copies from COGS library set)
Q: What is the major difference between the sensory systems of unicellular organisms, such as the protozoan Paramecium and vertebrates?
Rucci, Wray, Tononi, Edelman (1997) A robotic system emulating the adaptive orienting behaviour of the barn owl. Proc. 1997 IEEE Int. Conf. on Robotics and Automation, Albuquerque, New Mexico. pp 443-448. (copies from COGS library set)
Q: Assess the robot in terms of Pfeifer's design principles. Which have been implemented? What are the advantages of this particular multimodal architecture?
Agah, de Garis, Korkin, Simihga and Cho (1997) Architectural and functional specifications for a robot kitten "Robokoneko" to be controlled by a 10,000 evolved neural net module artificial brain. (also part of COGS library set) [Link] [Robokoneko Images] Q: Assess the "world's first artificial brain" in terms of Pfeifer's design principles. Which have been implemented? How would you characterise the control architecture? Assess Korkin's (New Scientist, 9-1-99) "What is do special about this neural network is a much higher degree of biological relevance" with reference to the Stein and Meredith chapter.
* Action Selection Seminar
All of the readings selected this week show different way to build systems that have multiple goals/tasks -- this is where the problem of action selection arises. Maes wrote an influential paper (her history was in Expert systems and, like Pfeifer and Steels, the, in part, rejection of them) -- she provides some definitions to think about. Scheier and Lambrinos worked in Pfeifer's lab and produced an excellent example of robot work, how does their work reflect Maes's. Seth, from Sussex, philosophically rejects (what did you expect?) the divisons that action selection places on a system. Blumberg considers action selection using ideas from the study of animals. Humphries uses reinforcement learning, is this formalism the way to go? And, if you haven't read it, the Brooks paper give the down and dirty on the subsumption architecture -- technically not action selection but why not?
All papers available from the SAB digital library -- read them with an eye to the various stategies to sequence behaviour between mutiple tasks.
Maes, P. (1991) A bottom up mechanism for behavioural selection in an artificial creature. Proc. SAB 90, pp 238--246
Scheier, C. and Lambrinos, D. (1996) Categorization in a real-world agent using haptic exploration and active perception. Proc SAB96, pp 65-74.
Seth, A. (1998) Evolving action selection and selective attention without actions, attention or selection. Proc SAB 5, pp 139-147
Blumberg, B. (1994) Action-selection in HAmsterdam: Lessons from ethology. Proc SAB94, pp 108-117.
Humphrys, M. (1996) Action-selection using reinforcement learning. Proc SAB96
Brooks, R. (1985) A robot that walks: emergent behaviors from a carefully evolved network. MIT AI Memo 1091
* Animals as Cost Based Robots Seminar
I promise, much less to read this week.
McFarland, D (1992) Animals as Cost-based robots. International Studies in the Philosophy of Science, 6, 133-53. Reprinted as Chapter 6 in "The Philosophy of Artificial Life" M. Boden (Ed), OUP 1996. Available from Celia in COGS library.
This paper looks like it may be missing the point, even so it makes some fundamental points.
Some questions to think about:
1. Is the frame problem a problem?
2. Do all robots have niches?
3. Are McFarland's type of cost functions sensible; are they related to ones used in GAs?
4. How autonomous should a robot be?
5. When should robots use implicit, embedded or explicit control systems?
6. Why distinguish between a cost and goal function. Could goal functions be learnt?
* Evolution of Communication Seminar
See this [file].
* An Engineering Spin-off: 'Ants'
See this [file].
* Essay discussion
As discussed in our last seminar the next seminar will comprise of short ( < 10 minute) presentations and then discussions of a topic that you think you would like to write about for the assessed essay.
There will be no (additional) reading for this seminar.