Robohub.org
 

The application of ‘elegance’ to machine behavior


by
30 January 2010



share this:

We all have some idea of what elegance means, whether our notion of it is tied up with silky evening dresses, polished wood and brass, chandeliers and stained glass windows, exotic carpets, and expensive sports cars, or with youthful bodies that are tanned and fit, knowing the local language well enough to use it sparingly with assurance, being appropriately dressed for the weather, good posture, fluid movement, a varied diet of moderate proportions, giving every task as much time as it requires, and so on.

 

Applying the notion of elegance to machine behavior may resonate for some and not for others. What could it possibly mean, elegant machine behavior, wouldn’t that be a contradiction in terms?

 

In this piece on another blog, I suggest that Apple should get into robotics, partly because to fail to do so would be to leave the largest looming growth market to others, and partly because I believe the company has something to contribute, something relating to elegance. I think Apple would set a high standard for machine behavior, and then exceed it, providing a tangible example of first-order elegance.

 

I say “first-order elegance” to suggest that there is also a “second-order” or “meta-elegance” that looks beyond present behavior to its ultimate effects. For example, formality may appear elegant, but if children are subjected to it all the time they may fail to develop emotional intelligence, an inelegant result.

 

As applied here, it is second-order or meta-elegance that is more important. It matters far less whether machines that tend land appear deft in their actions than whether the result of those actions appears more garden or desert-like. That’s not to say that first-order elegance is unimportant. Efficient movement, of the entire machine and of its parts, is an important aspect of cost-effectiveness, but efficiently producing a undesirable result gains nothing.

 

I believe that second-order elegance is achievable in this context, that machines can be programmed to understand complex living systems and nurture them, while raising food and fiber for market in their midst. If I didn’t believe that I would never have bothered trying to explain this vision of a greener future founded on robotics.

 

Reposted from Cultibotics.



tags: ,


John Payne





Related posts :



#ICML2025 outstanding position paper: Interview with Jaeho Kim on addressing the problems with conference reviewing

  15 Sep 2025
Jaeho argues that the AI conference peer review crisis demands author feedback and reviewer rewards.

Apertus: a fully open, transparent, multilingual language model

  11 Sep 2025
EPFL, ETH Zurich and the Swiss National Supercomputing Centre (CSCS) released Apertus today, Switzerland’s first large-scale, open, multilingual language model.

Robots to the rescue: miniature robots offer new hope for search and rescue operations

  09 Sep 2025
Small two-wheeled robots, equipped with high-tech sensors, will help to find survivors faster in the aftermath of disasters.

#IJCAI2025 distinguished paper: Combining MORL with restraining bolts to learn normative behaviour

and   04 Sep 2025
The authors introduce a framework for guiding reinforcement learning agents to comply with social, legal, and ethical norms.

Researchers are teaching robots to walk on Mars from the sand of New Mexico

  02 Sep 2025
Researchers are closer to equipping a dog-like robot to conduct science on the surface of Mars

Engineering fantasy into reality

  26 Aug 2025
PhD student Erik Ballesteros is building “Doc Ock” arms for future astronauts.

RoboCup@Work League: Interview with Christoph Steup

and   22 Aug 2025
Find out more about the RoboCup League focussed on industrial production systems.

Interview with Haimin Hu: Game-theoretic integration of safety, interaction and learning for human-centered autonomy

and   21 Aug 2025
Hear from Haimin in the latest in our series featuring the 2025 AAAI / ACM SIGAI Doctoral Consortium participants.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


 












©2025.05 - Association for the Understanding of Artificial Intelligence