|Section >> Self : Research|
|Structural coupling and the emergence of autonomous adaptive behaviour|
|Subsection >> select?|
|Implementation||Biosys : Phenomorph|
|Related work||GRNs : Structural Coupling / Control Systems : Embodiment : Alexander Riegler : Filippo Menczer : Barry McMullin : Behavioural robotics [Brooks : BEAM]|
adaptation and autopoiesis
embodiment and structural coupling
For example, being physically embodied in the world creates a very rich and complex relationship between a robot or biological organism and its environment—but it is this relationship that is important, which in the case of physical entities arises from the interactions between physical things under the laws of physics. The bare fact that a robot or organism is made of physical stuff is not significant for embodiment, except in so far as it impacts on this relationship.
A relational perspective on embodiment fits very neatly with structural coupling, which is a fundamentally relational, ontology agnostic concept that describes the significance of non-destructive mutually perturbatory interactions between two systems over a period of time. I decided that it would therefore be interesting to define embodiment as a situation in which structural coupling between a system (a network of two or more components arbitrarily identified as an entity by an observer) and its environment can occur:
See any of my publications from 1999 if you'd like more detail on this. In a nutshell though, the key points about this definition are:
The system's actions in any particular situation are not directly programmed or prescribed. What the system does at any moment in time via its effector surface is determined by its structure at that moment in time, linking sensory and effector surfaces. The structure is affected by both sensory surface (environmental) events and internal dynamics, allowing structural coupling between system and environment to occur.
Initial experiments evolving small environmentally-coupled GRNs shows similar reactive behaviour strategies emerging. The following graphs plot the movement of a simulated Khepera robot (Webots v2) over a 0.6 metre square flat surface featuring nothing but a single light-source. The robot is controlled in real-time by an evolved 5-gene GRN with a single regulatory site on each gene. The genome is evolving to respond to protein '0' produced by light detected on the left side of the robot and protein '1' produced by light on the right, in such as way as to maximise exposure to light by producing appropriate amounts of protein '6' (which determines the speed of the robot's left wheel) and protein '7' (determines speed of the right wheel). Again, a more detailed description of the model can be found here.
|Phenomorph||Phenomorph, mentioned in my 1999 papers, was an early attempt to investigate the relationship between system-environment coupling and emergent behavioural strategies. The idea was to use Cellular Automata (CA) or Boolean Networks (BN) coupled to a range of different environments (the 'real' physical world, a simulated physical world, the 'real' World Wide Web and a local hyperlinked HTML file repository) via appropriate sensory and effector surfaces to produce emergent chemotactic behaviour. The 'structural coupling to different environments' part wasn't too hard, but trying to get a 'standard' CA or BN to produce dynamics suitable for the emergence of meaningful behaviours was exceedingly frustrating, and so I turned to Genetic Regulatory Networks...|
The GRN model I use is similar in some respects to the one developed by Torsten Reil.
Peter Eggenberger uses GRNs as part of a development process to produce morphologies, with emphasis on biological realism; as does...
Sanjeev Kumar at UCL, who focuses on phenomena relating to pattern formation.
Josh Bongard uses GRNs as part of a development process to produce artificial agents.]
Wolfgang Banzhaf is doing work on modeling GRNs and their dynamics.
Stuart Kauffman thought of modeling GRNs before anyone else did.
|Structural coupling / control systems||
A number of people have developed systems and models that exploit system-environment coupling to produce control systems, though they don't necessarily talk in terms of 'structural coupling'.
Frank Daellart and Randall Beer have co-authored many interesting papers, often concerned with the coupling between neural network-driven agents and their environment, from a dynamical systems perspective.
Jens Ziegler (a man not afraid to use Java applets for site navigation) has evolved artificial chemistries, similar to biological signal transduction pathways, for robot control.
Tom Ziemke is quite the embodied man-about-town these days :-)
Rolf Pfeifer does lots of embodiment-related work, with a strong 'embodiment == being a physical thing' bias (well, from my perspective it's a bias).
Esther Thelen approaches Cognitive Science from the perspective of embodiment.
Alexander Riegler, at the Free University of Brussels, works on what he calls Constructivist ALife. His perspective is fairly similar to mine - recognising behaviour as a relational construct, and developing systems that exhibit emergent relationships with their environments as a result of their constituent plastic structures that perform sensory-effector correlations. However, the 'guts' of his system are very different, reflecting his background in cognitive science. His interest in Maturana and Varela's work is based on their contribution to the constructivist perspective.
Filippo Menczer's work in Genetic Algorithms recognises the role of complexity in the environment in the emergence of complex behaviours in the systems that evolve in those environments.
His approach is based on characterising problem spaces in terms of energy ('Latent Energy Environments'- LEE). Evolved organisms must maintain enough energy to continue their existence. Two consequences of this approach are, first, that fitness functions do not need to be imposed from outside of the system in an a priori fashion as is usually the case (this is an 'endogenous' fitness paradigm), and second, otherwise incommensurable environments can be compared via articulation in terms of latent energy. Menczer also eschews normalisation of fitness measures in populations, in favour of a more natural 'local fitness' model, well suited to varied environments.
InfoSpiders is an example application that illustrates the practical benefits of Menczer's approach, as a basis for distributed information seeking on the WWW. A population of agents get the energy they need to survive by finding web pages containing desired keywords. Energy is expended following URLs. This has similarities with the bacterial 'run-and-tumble' strategy, in that the result of this is that positive 'food' gradients in the environment are pursued.
McMullin's work focuses on formalising our understanding of Autopoiesis
as a process — currently somewhat 'wooly', and decidedly descriptive in
nature. Using the Santa Fe Institute's
simulation system, Barry re-implemented and has extended Varela's initial
Varela's initial and McMullin's subsequent simulations are based on the simulation of a qualitative chemistry, describing a range of basic elements, and rules for interactions between them. The goal is to understand the processes by which self-maintaining bounded structures (or just boundaries) arise.
Generally, embodied approaches to robotics exploit the relationship between robots and their environments to produce meaningful behaviours, rather than trying to stuff robots full of cumbersome and inevitably inadequate representations of their environments. The environment already does a perfectly good job of presenting itself - why re-present it? A grounding in physical reality is prioritised over abstract symbol manipulation. This approach has an awful lot in common with the European School of Philosophy (in contrast to the Western Analytic tradition, exemplified in symbolic AI) - particularly the phenomenology of Martin Heidegger and Maurice Merleau-Ponty. This perspective also motives some of the work being done at COGS in Sussex (see in particular EASy - the Evolutionary and Adaptive Systems Group, more links here.)
Such approaches present human beings as being fundamentally 'in the world', in contrast to the mind-body dualism presented by the father of Modernism, Rene Descartes—which begins with rational thought, and then contemplates its relationship to the material world. This is a direct analog to symbolic AI, which takes formal, abstracted rationality and the mechanisms thereof as its starting point in the development of systems that relate meaningfully to the world and its inhabitants.
BEAM robots, pioneered by Mark Tilden, effectively take Brook's approach to an extreme—with a great deal of success.
BEAM robots are constructed solely from simple electronic components, such as resistors, capacitors and transistors. Their behaviours effectively arise as a result of the sensory-effector correlations performed by these simple components. They are totally autonomous, in the sense that they are guided only by their own structure and the dynamics therein, and typically have their own means of generating power, in the form of solar cells.
BEAM robots are extremely cheap to build (allegedly around £20 for the parts for a simple 'SunEater'), placing this technology within the reach of thousands of hobbyists, speeding the evolution of this field...
Tilden has also developed a basic but functional nervous system (a 'nervous net') allowing complex behaviours, but employing just a handful of basic components connected in a ring.
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