Andy Clark. Ch1.pt1 Supersizing the Mind “A Walk on the Wild Side”

summary by Corry Shores
[Search Blog Here. Index-tags are found on the bottom of the left column.]
[Central Entry Directory]
[Posthumanism Entry Directory]
[Andy Clark, Entry Directory]
[Andy Clark, Supersizing the Mind, entry directory]

[My own commentary is in brackets. All boldface and underlining is my own. Extra spacing between paragraphs follow the paragraph divisions in the original text.]

Andy Clark

Supersizing the Mind:

Embodiment, Action, and Cognitive Extension

Ch.1
The Active Body

Part 1.1
A Walk on the Wild Side

Very Brief Summary:
Robots are more efficient and natural when they are designed in a way that makes use of available environmental influences.

Brief Summary:
Robots can produce more natural and efficient movements when they involve: 
1) passive dynamics: “the kinematics and organization inhering in the physical device alone”, for example morphology and distribution of weight;
2) ecological control: “part of the “processing” is taken over by the dynamics of the agent-environment interaction”;
3) the principle of economic balance: “first . . . that given a certain task environment there has to be a match between the complexities of the agent’s sensory, motor, and neural systems . . . second. . . . that there is a certain balance or task-distribution between morphology, materials, control, and environment”; and
(4) nontrivial causal spread: “which  occurs whenever something we might have expected to be achieved by a certain well- demarcated system turns out to involve the exploitation of more far-flung factors and forces. For the Mississippi alligator, the temperature of the rotting vegetation in which it lays its eggs determines the sex of its offspring.”

Summary

Clark discusses robots that walk like humans. One is Honda’s Asimo. (3c)

(from page 4)

But it is not energy efficient compared to human energy consumption while walking. (3d)

Clark explains:

Whereas robots like Asimo walk by means of very precise, and energy-intensive, joint-angle control systems, biological walking agents make maximal use of the mass properties and biomechanical couplings | present in the overall musculoskeletal system and walking apparatus itself. Wild walkers thus make canny use of so-called passive dynamics, the kinematics and organization inhering in the physical device alone (McGeer 1990). Pure passive-dynamic walkers are simple devices that boast no power source apart from gravity and no control system apart from some simple mechanical linkages such as a mechanical knee and the pairing of inner and outer legs to prevent the device from keeling over sideways. Yet despite (or perhaps because of) this simplicity, such devices are capable, if set on a slight slope, of walking smoothly and with a very realistic gait. The ancestors of these devices are, as Collins, Wisse, and Ruina (2001) nicely document, not sophisticated robots but children’s toys, some dating back to the late 19th century. These toys stroll, walk, or waddle down ramps or when pulled by string (see fi g. 1.2). Such toys have minimal actuation and no control system. Their walking is a consequence not of complex joint-movement planning and actuating but of basic morphology (the shape of the body, the distribution of linkages and weights of components, etc.). [3|4]

Robots with more human like morphology make more fluid movements than ones using powered operations and joint-angle control. (5)

Powered locomotion with passive dynamics can produce efficient and fluid robot motion. (5)

Such solutions also make use of ecological control.

an ecological control system is one in which goals are not achieved by micromanaging every detail of the desired action or response but by making the most of robust, | reliable sources of relevant order in the bodily or worldly environment of the controller. In such cases,

part of the “processing” is taken over by the dynamics of the agent-environment interaction, and only sparse neural control needs to be exerted when the self-regulating and stabilizing properties of the natural dynamics can be exploited. (Pfeifer et al. 2006, 7) [5-6]

Clark offers the example of the robot Puppy. (6b.c)

According to Pfeifer and Bongard (2007), the principle of economic balance states

first . . . that given a certain task environment there has to be a match between the complexities of the agent’s sensory, motor, and neural systems . . . second. . . . that there is a certain balance or task-distribution between morphology, materials, control, and environment. (123) [7b]

Clark explains:

The “matching” of sensors, morphology, motor system, materials, controller, and ecological niche yields a spread of responsibility for efficient adaptive response in which “not all the processing is performed by the brain, but certain aspects of it are taken over by the morphology, materials, and environment [yielding] a ‘balance’ or task-distribution between the different aspects of an embodied agent” (see Pfeifer et al. 2006). In such cases, the details of embodiment may take over some of the work that would otherwise need to be done by the brain or the neural network controller, an effect that Pfeifer and Bongard (2007, 100) aptly describe as “morphological computation.” [7b.c]

Clark says such passive-dynamic systems exhibit nontrivial causal spread, which

occurs whenever something we might have expected to be achieved by a certain well- demarcated system turns out to involve the exploitation of more far-flung factors and forces. For the Mississippi alligator, the temperature of the rotting vegetation in which it lays its eggs determines the sex of its offspring. This is an example of nontrivial causal spread. When the passive dynamics of the actual legs and body take care of many of the demands that we | might otherwise have ceded to an energy-hungry joint-angle control system, we likewise encounter nontrivial causal spread. (7-8)

Causal spread can come about from evolution, engineering, or a combination of the two.

For example, some control systems are able to actively learn strategies that make the most of passive-dynamic opportunities. An example is the Toddler robot, a walking robot that learns (using so-called actor-critic reinforcement learning) a control policy that exploits the passive dynamics of the body (fig. 1.5). The Toddler robot, which features among the pack of passive-dynamics- based robots described in Collins et al. (2005), can learn to change speeds, go forward and backward, and adapt on the go to different terrains, including bricks, wooden tiles, carpet, and even a variable speed treadmill. And as you’d expect, the use of passive dynamics | cuts power consumption to about one-tenth that of a standard robot like Asimo. (8-9)

(from page 8. fig 1.5, The Toddler robot, by Russ Tedrake, Teresa Zhang, and H. Sebastian Seung, photo by Zhang)

Andy Clark. Supersizing the Mind: Embodiment, Action, and Cognitive Extension. Oxford / New York: Oxford University Press, 2008.