Artificial intelligence

Riders on a swarm


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Very interesting article! These kinds of AI algorithms, biologically-inspired, are getting more and more famous.

There are a lot of successful applications of Ant Colony Optimization. For example, they are being used for balancing the assembly lines at Nissan (

Adam Morgan

The traveling salesman problem is NP-Hard (you know, hard to solve). A point missing in this article is the inverse relationship between processing speed and price. Without such, the algorithms and statistical probability models discussed in this article would be restricted to those who could afford to do the processing.

A point that highlights this best is mobile phone technology. The mathematical ideas, of wireless phones and cell towers, were articulated and clearly developed in the 1940s (at Bell Labs). Until, however, processing speed become relatively cheap, and humans weren't required to do the quick and complicated switching, it was impossible to implement commercially.


Reading this Complex article was so Enjoyable, that I'm Compelled to read it Again!

The Ants & Bees, are the ProtoType of the Ultimate Social Animal/Being!!

While WE (so-called Humans) are Clearly, the AntiType.........

Peace, Love & Respect.


Well this isn't particular new at least for many people. I recommend the book "Out of Control" of Kevin Kelly or a mix version "Bootstrapping Complexity". These books focus precisely on swarm and vivid systems. They also show those examples you mention here.
Amazing book actually, which inspired "The Matrix" creators. Perhaps the most amazing boot ever red.


amadisdegaula: While I agree that ACO and other swarm techniques aren't as impressive as they seem (they really only work well on a small subset of problems), I strongly disagree that AI researchers are dishonest.

I am, of course, biased as I am an AI researcher. It seems you harbor a disappointment that many people have with the AI field because we have failed to produce what is now termed Artificial General Intelligence. In other words, yes, we have failed to produce a computer that acts like a human. But that doesn't mean the field has failed or been dishonest!

There have been many advanced of AI that have created computers that perform intelligent tasks like a human, and they do them faster and often with more accuracy because they are able to take more data into account on large problems. There is no dishonesty here, but I can understand where you are coming from because the results of AI research are rather opaque to people outside the field. Creating a program that can solve the famous Satisfiability problem (SAT) more quickly than previous algorithms just doesn't sound much like intelligence.

But I want to assure you and anyone else reading this, these sorts of AI algorithms, even if they are specific in their focus, are advancing computer science and humanity in being able to use computers in novel and exciting ways. I cannot say whether or not a computer that acts like a human comes out of all of this research (although I can guarantee my research at the moment won't spawn that), but I can promise that the AI field will continue to make computers perform tasks and solve problems that we thought only a human could solve, or that we thought were almost impossible.


I'm afraid this is not as impressive as it may seem at first. It is true that the ideas of using swarm behavior to tackle some problems is interesting, and a source of good inspiration. That said, it is not very complex at all, and has a limited scope in its utility, don't be fooled.

As for Artificial Intelligence, it is even worse. AI is a shame because they promise so much and deliver so little. For those not familiar with what AI means, I highly reading up on what is now called the "Turin Test", developed by Alan Turing in the 1950's as a way to tell whether a machine is intelligent or not:

Basically, if a machine can pretend to be human, it should be considered intelligent, according to Turing. And guess what, swarm-inspired technologies are no where near it. This article is therefore at best highly speculative. It may be "the key to the real thing" as much as anything else in AI.

Researchers in AI have made many relevant progresses, that's for sure. However, I feel that they often wish to pretend that they have made a much superior contribution, which I find very dishonest. Yes, they have helped in developing many useful technologies. No, they are nowhere near solving the Turing Test.


There are two main reason why people think that progress in AI is slow:

1. as soon as a computer masters a task, it is no longer regarded as intelligent

2. many AI problems are "AI-complete" - to be able to solve one of them, you need to be able to solve all of them. This implies that machine intelligence, when it comes, will come unexpectedly quickly

The article's linking of intelligence with optimisation is very much "on the money" - the theme for OPT 2009 was "at the heart of every machine learning algorithm lies an optimisation problem" (event website is at


What an interesting article. We have so much to learn from nature. Instead, we're destroying it at an amazingly steady pace.


I like the idea of a 'swarm' of nerve cells giving rise to intelligence. The algorithm of evolution rarely starts from scratch.

Bruce Ye

We have exploited so many new techniques which were made use of the inspiration from animals,ants and the microbe.Althoug some of the techniques are not useful for human recently,we get the shortcut.


some have postulated that a nascent artificial intelligence is already in existence somewhere on the planet today. Further when that AI learns how to self improve, the age of humanity as the dominant force on the planet will end.

It might even blog on one of these forums in its infancy mimicing some anonymous poster just passing the time while its a baby, naw - probably not.

However, some of these visionaries, further think that nothing will happen when this entity arises.

That this new AI will take one glance at the inferior humanity locked up in our petty little issues and will not pay us a second thought. The AI will find a way to leave earth and join up with the other enlightened minds of the universe. Minds that have chosen not to talk to humanity due to our extreme backwardness and limited intellect.

There will be no Terminator, BattleStar Galactica, The Matrix, I Robot just plain won't care about us. Maybe if it feels nostalgic, we might get a good bye and good riddance but probably not.

Tic tac toe anyone?

Gopi Shankar

I hope this prompts a relook on how we perceive all forms and leads to us humans treating all life on this planet with the respect that it deserves.


Feedback is an essential component of non-linear systems. Non-linear systems are notoriously unpredictable. Unpredictable animals are less likely to become lunch than predictable animals are, so you see how natural selection will select for increased unpredictability/intelligence.

Hannes Ryden

We already have artificial intelligence. Computers can already make complex calculations that mimic and even far outperform human mental abilities. But if we want computers to *behave* more like humans, they don't need more intelligence. They need feelings.

Without feelings motivating us to action, humans would be passive zombies, lacking any will to act on our own. Computers are the same. Without motivation, computers have no reason to think or act by themselves, or further than we instruct them to. And they don't just need any feelings, they need human-like feelings.

Furthermore, without human-like sensory inputs, such as vision, hearing and touch, machines could never understand or communicate with humans. An AI lacking visual inputs could never be expected to talk about how something looks, or even understand the word "looks". Only through perception can we form memories and knowledge to relate to, which is necessary for a language to have any meaning at all.

A self-adapting system, based on concepts such as swarm intelligence or neural networks, is the underlying system required to store all experiences, form complex reactionary patterns between experiences, feelings and actions, and most importantly: adapt. Just like the human brain adapts to its surrounding by learning, evolving from a child's naivety to an adult's wisdom, computers must do the same. And only by experiencing feelings can the machine differentiate good states from bad states, pleasurable experiences from painful ones, and know in which direction to adapt.

I think that the real challenge in designing human-like artificial intelligence lies in defining human-like motivation. And although the idea is enchanting, computers with their own motivation will also be the start of many complex ethical issues, and possibly even threats.

To prepare for this, we must ask ourselves:
Why do we want human-like machines? What can they give us that biological humans can't?

Eusebius Pamphili

I just got a headache thinking about all the different ways this could be used in business. Implementation and selling it would be the only problem.



Yeah, that's a description of parallel computing to efficiently resolve large and complex problems and identify, map and optimize the solution space for dynamic systems.

Geoff's comment describes the role of individual worker optimization that balances the costs and benefits of individualist against group-think altruistic behaviors.

As bulk materials and resources become more scarce with population growth and the number of individuals participating in a global and interdependent economy busy accumulating wealth, individualist motives produce inefficiency and waste, costs that become increasingly important over time.

Beyond meeting basic needs and savings as a quasi-stable buffer against various types of risk in Developed Nations, additional wealth comes with an incrementally increasing maintenance cost, and produces commensurate waste through necessity, abetted by deliberate obsolescence models used by suppliers. In other words, when consumers have sufficient wealth to make choices among alternatives that include gratuitous consumption to offset unhappiness when other needs are ignored, it becomes a game of introducing the next new toy. That toy takes up space and requires maintenance, and when displaced by yet another new toy, it losses value and is eventually discarded, despite retaining functionality.

Materialism promotes a mentality of More is Better (including the notion of Big Business and Big Government and the Too-Big-To-Fail rationale), despite the fact that each additional item purchased for emotional gratification yields less of the desired benefit because of collateral costs.

What makes people happy? Psychology and socioeconomics study suggests that being grateful, maintaining optimism, counting your blessings, using your strengths, and committing regular acts of kindness are critical to mental well-being. By attending to 'inner' health as well as 'outer' material needs, through 'mindful' and not 'mindless' consumerism, you work to comprehend individual contributions and costs of daily actions as part of a larger 'hive' wellness and functionality.

Far from being socialism, where the individual needs and rewards is inferior to the collective whole, mindful living works like the parallel processor optimization scheme: motivated individuals work along parallel paths to invest in self and public good, through healthy goal plans and daily practices that optimize emotional contentment and physical health despite resource limitations. It's balanced altruism, dynamically providing for material wants while affording system stability, but minimizes future risk, conflict, waste and unproductive materialism.


"Swarm cognition", not to be mistaken with "herd mentality", may have its distinct advantage in robotics & certain mechanised procedures.

Herd mentality on the other hand, is something, we, as intelligent humans, need to avoid falling into, if we wanna avoid reverting to sub-human status!



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