It starts out like this -- our body parts are already a swarm. We take it for granted that our body parts know where they are and what they're doing, and can talk to each other. "Stereotypical body control is taken care of by neural subsystems so that the conscious cognitive system can deal with more complex world dynamics." -
link
What we don't take for granted, and what we might even find uncomfortable to imagine because it means radically redefining the human condition, is that our assemblage of body parts will one day extend to the technosphere of nanobots, controlled not by us alone but by an emergent swarm cognition consisting of all the nodes in our extended neural network, and all of this wired directly into our own big bundle of blinking neurons in our head.
But then, in the same way these "nodes" of flying, crawling, swimming bots will join with us, our body parts will disarticulate to become part of the greater network. In the beginning, we will need "humans-in-the-loop," but eventually, we will need bigger and more centralized centers of control to interact with control the decentralized swarms. There will be humans in the loop, only a bit more efficient, so that one human will control multiple body-swarm entities. Your hands will no longer be your own. We will share everything. Today, your privacy is gone, tomorrow, the body itself.
A theoretical approach for designing a self-organizing human-swarm system
Aug 2021, phys.org
Bio-inspired metaphor for design, the swarm-amplified human, which essentially proposes that the swarm should self-organize itself into and act like human body parts."
The paper highlights the potential benefits of using human state classification as a control input fed to a robot swarm, rather than having a human user controlling the swarm at all times.
"Designing robot swarms that are an extension of the human body relates to integrating neural logic into robot swarms on the network level, which has received only limited attention so far," Hasbach said. "We have proposed some ideas on how robot swarms could be thought of as neural systems."
^That's just the press release for this theoretical framework. I'd like to paste a few lines from the paper itself because if I didn't tell you, you might think it came from a good scifi novel. In other words, you can't make this stuff up:
Because no holistic theory has been explicitly formulated that can inform how humans and robot swarms should interact.
Joint human–swarm loops, that is, a cybernetic system made of human, swarm and interface.
An intelligent system that balances between centralized and decentralized control.
The robot swarm should be integrated into the human’s low-level nervous system function.
The swarm amplified human treats the swarm as an extension of the human nervous system, integrated at low-level sensory–motor behaviour
Interfacing at the low-level nervous system means essentially two things (Figure 9). First, as said before, low-level stereotypic sensory–motor control often feels automatic to the conscious mind. When walking down the street, you rarely think about walking. Therefore, the (cognitive) state of humans should be translated by the interface into commands for the swarm clusters. This is referred to as passive or implicit interaction, that is, unconscious control, which can be contrasted to active/explicit control (e.g. deliberate gesture control).
This feeling of being in control over the swarm clusters (alias artificial body parts)
The SAH [swarm amplified human], therefore, relates to the notion of a cyborg that ‘[…] deliberately incorporates exogenous components extending the self-regulatory control function of the organism in order to adapt it to new environments’
-Clynes, M. E., Kline, N. S. (1960). Cyborgs and space. Astronautics, 5, 26–27.
Rather than claiming that neural networks and biological swarms share the actual same computational basis, we argue that both can be modelled as self-organizing systems. Thus, both humans and swarms are abstracted into one common computational reference frame to integrate the swarm at the low-level of neural sensory–motor loops.
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| swarm amplified human - figure 11 |
Humans also need training to learn sensory–motor patterns for their real body parts. No human baby is able to walk after birth... Similarly, the operator should be exposed to different situations so that he is able to develop an intuition of swarm dynamics as well as how his own states influence these dynamics.
A more biologically plausible and more efficient algorithm may be a searching robot chain that originates from the human, similar to growing biological axons that are guided by molecular cues.
Human agent moving through a swarm gradient.
By convergence, global information about the environment can be estimated by the swarm connectome and provided to the human, similar to sensory upstreams in the biological nervous system.
To include the swarm in the human’s nervous system, the brain must be tricked into integrating the swarm into its body representation. This is achieved if the human operator has the illusion that the swarm feels like part of himself, if it feels like an artificial body part.
In the future, Tom may be equipped with an advanced brain–computer interface technology that provides high-resolution classifications of cognitive states and adapted sensory–motor signals. This could allow him, for example, to feel the location (i.e. the direction and the distance) of a victim, alike to having a sixth sense, while allocating more robots to the estimated location of the victim, similar to closing your hands around an object.
Rather than being the target of the interaction, the swarm should self-organize as the interface between the human operator and relevant features of the environment. This mimics the formation of neural pathways in the nervous system that are tuned to relevant environmental stimuli.
Notes:
via Fraunhofer Institute for Communication, Information Processing and Ergonomics (FKIE) and University of Bonn in Germany: The design of self-organizing human-swarm intelligence. Jonas D Hasbach, Maren Bennewitz. Adaptive Behavior (2021). DOI: 10.1177/10597123211017550
New Word:
Excursively - given to making excursions in speech, thought, etc.; wandering; digressive. Example: Robustness and scalability is created by treating the swarm as a distributed neural machinery that excursively relies on local interactions.
Post Script:
"So quite ya yappin' fore I get to clappin'
And have your body parts mix and matching fella"
-What Happened to That Boy, Birdman feat. Clipse (Neptunes), 2002
Post Post Script:
Happened to see this from an older post, but it doesn't hurt to plaster this one all over town until it gets old (it never gets old)
Dec 2011, Nature
