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Darkly Wise and Rudely Great
Imagine you are a great historical scientist and discover a disturbing truth about nature. Perhaps you discover that the world is not flat like a map, but in fact round like a tomato. Or, maybe you discover that instead of the Earth having a special place at the center of the universe, it is a just an ordinary rock floating in space – distasteful and troubling revelations.
The naturalist, Charles Darwin, was in such a situation in 1859. Although a devout Christian, Darwin’s pursuits led him to discover the mechanism by which life on Earth developed from a common ancestor, leading to the obvious conclusion that humans evolved from their closest relatives, the great apes. It was the most disgusting idea of the century, and he was personally troubled by it for the rest of his life.
The path Darwin’s life took made him a likely candidate to discover the mechanism of evolution. He had an obsessive-compulsive personality, avidly collecting and cataloging beetles and other insects around his home. And, his own grandfather, Erasmus Darwin, had already put forth the idea of common ancestry in a poem 60 years earlier:
“The Temple of Nature”
Organic life beneath the shoreless waves
was born and nors’d in ocean’s pearly caves;
First forms minuk, unsceen by spheric glass,
move on the mud, or pierce the watery mass.
These, as successive generations bloom
New powers arquire and larger limbs assume
whence countless groups of vegatation spring.
And breathing realms of fin and feet and wing.-Erasmus Darwin 1802
Most auspiciously, his family was affluent. His father, frustrated with Charles’ unending curiosity and lack of direction, eventually agreed to let him travel abroad with the HMS Beagle even though he considered it to be a complete waste of time. Darwin’s writings of the journey solidified his position as a well respected and well connected member of the scientific community.
He became close friends with Charles Lyell and John Dalton Hooker, the most influential geologist and botanist of his time respectively. Through Lyell, he came to see the natural world as a gradually changing process. Hooker was a trusted confidante with whom he could share some of his troubling revelations. After writing his first essay on natural selection, Darwin told Hooker it was like “confessing a murder”. Hooker gave him the calm, critical feedback Darwin needed to proceed.
The final push came from the naturalist Alfred Russel Wallace who wrote his own version of natural selection in 1858, ahead of Darwin. Both Darwin and Wallace had been inspired by the ideas of the Reverend Thomas Malthus who promoted the idea that population outstrips food supply, and both came to similar conclusions about how this creates selection pressure in nature. Hooker and Lyell arranged to have some of Darwin and Wallace’s ideas presented at a conference in 1858. This inspired Darwin to kick into high gear and finish “The Origin of Species” within a year, unleashing the most consistent and comprehensive explanation of natural diversity ever conceived, then and since.
Darwin did not doubt the literal translation of the bible as a young man, but bravely came to question the nature of the Christian God after observing nature in detail. His attitude was well summarized by his observations of the Ichneumonidae wasp. He wrote:
“I cannot persuade myself that a beneficent and omnipotent God would have designedly created the Ichneumonidae with the express intention of their feeding within the living bodies of Caterpillars, or that a cat should play with mice.”
-Charles Darwin 1860
Like Copernicus’ realization 350 years earlier that the Earth was not at the center of the universe, Darwin’s theory of natural selection pressed heavily against the religious views of his time. Though the religious conflict was never fully resolved in his own mind, Darwin lived to witness his theory gain acceptance in the scientific world and among much of the general public before his death in 1882.
Darwin might have found some solace in the poet Alexander Pope who foresaw the impingement of science upon religion. In “An Essay on Man”, Pope describes Man as passionate and ignorant, existing between God and beast, and that science is a valuable tool for understanding our nature, but not useful in answering religious questions:
Know then thyself, presume not God to scan,
The proper study of mankind is Man.
Placed on this isthmus of a middle state,
A being darkly wise and rudely great:
With too much knowledge for the Sceptic side,
With too much weakness for the Stoic’s pride,
He hangs between, in doubt to act or rest;
In doubt to deem himself a God or Beast;
In doubt his mind or body to prefer;
Born but to die, and reas’ning but to err;
Alike in ignorance, his reason such,
Whether he thinks too little or too much;
Chaos of thought and passion, all confused;
Still by himself abused or disabused;
Created half to rise, and half to fall:
Great lord of all things, yet a prey to all;
Sole judge of truth, in endless error hurl’d;
The glory, jest, and riddle of the world.- Alexander Pope 1734
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Avida
Self-replicating programs have been around for a while. The idea was first conceived by John Von Neumann in 1948 as a thought experiment. The first real instance was a game called Core War developed in the early 80s where programmers would write code to compete for sections of the computer’s memory. The best strategies were those that copied themselves, but these programs were fragile – change one piece of code and they would would cease to function.
Tom Ray’s Tierra in 1991 added some stability to the concept of mutation in a digital environment and showed that evolutionary processes previously only seen in nature can take place in the digital world. This eventually led to the “killer app” of self-replicating program research environments, “Avida”, developed by Charles Ofria at Michigan State University’s Digital Evolution Lab in 2000. Below is an animation showing successive generations of Avida organisms (Avidians) taking over the population as a sample evolution progresses:
At the 2010 Artificial Life XII conference in Odense, Denmark, the MSU team presented a paper describing some of their most recent work, including digital creatures that evolved the ability to follow paths along a grid. The environment was strewn with clues, signposts indicating which way the path would go. After tens of thousands of generations of evolution, the Avidians evolved reflex actions which successfully interpreted the signs as either “turn left” or “turn right”, giving them a survival advantage.
A program with just reflex actions can do quite a lot in a complex environment. What about using “volatile memory”, not just knee-jerk responses to the environment, but ones that depend on context? To encourage the evolution of volatile memory, the researchers put sign posts on the grid that symbolized “repeat last action”. The MSU team showed the Avidians were indeed able to take advantage of this information by evolving the ability to remember their last action.
The ability to remember and recall a single variable in the environment appears trivial, especially for a computer program, but the significance of this research is that no one programmed this behavior. The code which navigates the path and uses volatile memory to its advantage bubbled up from the raw evolutionary stew acting against a carefully crafted artificial environment that allowed such evolutionary pressure to exist.
There are many interesting questions here: Under what circumstances does evolutionary pressure tend to favor the development of micro brain structures? How can we configure artificial environments to evolve more complex bottom-up brains? How does the evolution of such structures manifest in nature?
Avida is a robust open-ended research tool and it is likely we will see many more groundbreaking projects coming from this platform for some time.
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The First Programmer
In 1822, the Englishman Charles Babbage conceived of a mechanical device called the Analytical Engine, a theoretical automated abacus of sorts that could perform calculations while powered by a crankshaft. He never built his machine, but his close friend Ada Lovelace, a brilliant mathematician, understood the implications of Babbage’s work. She designed software for the machine to compute Bernoulli numbers, and so is credited as being the very first programmer.
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The Edge of Life
In 1971, computer networks were a relatively new concept, and so it occurred to Bob Thomas, an engineer working at BBN Tech that it would be neat to write a program than could traverse these networks on its own, forever copying itself onto other machines. The “Creeper” was born. Unknowing users would login to their terminals and be presented with the text “I’m the creeper, catch me if you can!”. After logging in, the program would attempt to connect to other machines on the network and move itself to a new system. Although the term “computer virus” had not yet been coined, Bob Thomas had had managed to create the first one. He later wrote the complimentary “Reaper” program to seek out and shut down any Creeper programs out in the network.
Frederick Cohen’s research at USC in 1983 brought the idea of a computer virus to the mainstream. He developed a program that attempted to spread by attaching itself to commonly used programs on a shared computer system. Within minutes, Cohen’s program would spread through the file system and gain complete control. Cohen believed that his program was alive in the literal sense because it met the requirements for life: it was a pattern capable of reproducing, it could make use of the metabolism of its host (the computer), and it adapted to its environment, installing itself opportunistically.
The “Strong Claim” of Artificial Life says that any definition of life that includes all biological forms will necessarily include some computer-based systems as well, and these systems must therefore be considered actually alive. When the field of Artificial Life was formed in 1987, scientists agreed that computer viruses were indeed the most likely candidate to meet the strong claim. The opposite “weak claim” states that no matter how lifelike programs become, they will only ever be simulations of life, not instances of it.
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Flock of Boids
Large flocks of birds appear to display a collective intelligence as they fly in an organized fashion with an apparently singular motive. Starlings in particular have been observed in flocks reaching hundreds of thousands of individuals generating amazing patterns in their group movement as shown in the video below.
Artificial Life researchers get very excited when complexity can be shown to emerge from very simple rules. One of the early examples of this was developed by Craig Reynolds as part of the 1987 SIGGRAPH conference with a program he called BOIDS. With BOIDS he demonstrated that flocking behavior can emerge naturally if every individual BOID followed three simple rules:
- separation: steer to avoid collisions
- alignment: head in the same direction as your neighbors
- cohesion: head towards the center
BOIDS is an excellent example of emergent behavior, and since been adapted for use in computer graphics and special effects, its first use being the 1992 film “Batman Returns” to render bat swarms and penguin flocks.
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The Dynamical Approach
In the field of Artificial Intelligence, it is assumed that the brain is a type of computer: it can read inputs from the senses, represent the world symbolically, compute plans, and take action. Cognitive processes are represented as a kind of flow chart. But does the brain really function like a computer? The computer model does not take into account the fact that the brain activity is a continuous, time-dependent process. Unlike a computer program which is fed a problem, computes an answer at some future time, then waits for the next problem, the human brain may be more like a “dynamical system” that is continuously processing and interacting with the environment in real-time while maintaining a stable but ever-changing state.
The philosopher Tim van Gelder used the following example to contrast the computational vs. dynamical descriptions of cognition. Consider the problem of regulating the speed of a steam engine. Steam pressure driving the engine may fluctuate and we need to make sure it turns at a constant speed. The computational approach would involve adding sensors to measure the current speed of the engine, feeding this data into software that represents the engine symbolically with variables and equations, computing the required throttle adjustment, and finally at some later time, signalling the throttle to open or close by a specific amount. This process would then repeat ad infinitum.
The dynamical approach to regulating a steam engine was in fact invented in 1788 by James Watt and is called a centrifugal governor. The engine is connected to a spindle that spins with the engine. The spindle has arms with weights hanging off them such that when the engine speed increases the spindle spins faster causing the weights to move outward due to centrifugal forces thus raising the arms. The arms are connected to the throttle such that as they raise up, the throttle begins to close. Similarly, when the arms move to a lower position (when the engine is spinning slowly) the throttle opens up. The result is an engine that works at a constant speed despite the changes in input energy.
Van Gelder points out that this solution is remarkable because it solves a seemingly computational problem in a non-computational way: there is no flowchart, no procedure or steps to complete, and no symbols. More importantly, the system responds in real-time to changes in the environment without waiting for computations to complete. By using a direct, real-time, continuous feedback loop (the engine controls the position of the arms, and the position of the arms controls the engine) the system maintains stability. Is it then possible that the human brain, a seemingly computational device, can actually be explained in a similarly non-computational way using a dynamical approach?
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The Pooping Duck
The quest to create mechanical creatures goes back to the ancient Greeks, but the concept experienced a revival at the end of the Renaissance. Around 1640, Descartes put forth the idea that the human body works like a machine and could be understood as such. The idea that nature can be viewed as a mechanical process was solidified in 1687 when Newton published his Principia. In it, he describes in detail how nature follows mathematical rules. Indeed, Newton viewed the universe as a massive clock built by God and set into motion. These ideas were a precursor to the Industrial Revolution and also made clockwork automata a fad in Europe in the early 18th century.
Jacques Vaucanson [1709-1782] was an unsung hero of the Industrial Revolution. The invention of the mechanical loom is usually credited to Joseph Jacquard, but it was Vaucanson who first came up with the idea of using punchcards to store textile patterns, a technology that would be used in the first computers 200 years later. Vaucanson also build the first functioning automaton, a mechanical flute player that emulated a human being. The lips and fingers of the player moved naturally on the flute, and he painstakingly copied the musculature and breathing of a human. Its breath could be felt emanating from the mouth as it played.
After the success of the flute player, Vaucanson built an automated tambourine player, and finally his most famous work, a mechanical duck in 1738. The duck was made of gilded copper and contained over 400 moving parts hidden from view. The duck could drink, eat, quack, splash about and even defecate. Vaucanson used a new high-tech material, rubber, to design the ducks digestive system, and thus developed the world’s first flexible rubber tube. It was later discovered that the duck did not actually defecate as the “feces” were stored in a separate compartment, but this did not diminish the magnitude of his masterpiece.
Vaucanson was a showman and toured througout Europe with his duck, charging admission and wowing audiences with his creation. No-one had ever before seen a mechanism which appeared so alive. He eventually caught the attention of the French government who hired him as inspector of the manufacture of silk. It was during this time he invented the first fully automated loom which used punch cards, the machine later improved upon by Jacquard. The silk workers of Lyon rebelled against Vaucanson’s automatic loom by pelting him with stones in the street, insisting that no machine could replace them. This foreshadowed the later anti-industrial sentiment of the Luddite movement in Britain. Vaucanson’s original automata were lost to history, but a replica of the duck is now kept in the Musee des Automates in Grenoble, France.
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The Luke Arm
In 2005, the U.S. Defense Advanced Research Projects Agency (DARPA) sought out the greatest inventor in the country. Too many soldiers were coming home from Iraq with missing limbs, and DARPA was determined to give them the best treatment and technology available. They approached prolific inventor, Dean Kamen, and gave him the challenge of building a lightweight prosthetic arm within 2 years that would have enough dexterity to allow the wearer to pick up and a grape without damaging it. Kamen was initially deterred by the ambitious timetable, but eventually decided it had to be done. At his DEKA Research labs, Kamen and his team developed what they called the “Luke Arm” within 18 months. The device is named after Luke Skywalker who, after losing a duel with Darth Vader in “The Empire Strikes Back”, was given a prosthetic arm that appeared so tightly integrated with his real body that he could trivially operate his new hand just as he did before.
Tight integration means there must be many ways for the user to easily send commands to the prosthesis so that it becomes a natural extension of their body. The Luke Arm can be controlled by nerves, muscles, and foot pedals. A new user can comfortably control the artificial limb after just 10 hours of practice. The arm, loaded with processors, also has haptic feedback. Pressure sensors on the fingers send signals back in the form of vibrations, so the wearer can tell how hard they are grasping an object (a requirement for passing DARPA’s “grape test”). So far, DARPA has invested over $70m in the venture. The arm will be commercialized once the FDA conducts clinical trials and grants approval.
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Tierra
Tom Ray was a tropical biologist who conducted research in the Costa Rican rain forest from 1974 to 1989. His research focused on the ecologies and evolution of various species living there. Eventually he realized he there was a problem with studying evolution in the wild: it occurs far too slowly to actually observe it. He decided therefore to study evolution in a much faster medium, the digital computer. In 1991, he joined forces with the Santa Fe Institute in New Mexico to develop an evolutionary software platform called Tierra.
Genetic Algorithms, programs that simulate evolution to solve a specific problem, had already been well established, but Tierra was different. It wasn’t optimizing anything in particular. Small chunks of machine code were simply left on their own to replicate and compete for access to the CPU, and that was all. Occasional mutations in the copying process allowed evolution to take place. But, this wasn’t a simulation of evolution, these entities were actually evolving. What emerged from Tierra surprised Tom and most of the Santa Fe research team.
The first thing Tom noticed was that these replicating programs became smaller and smaller. A smaller program could replicate faster and so had an advantage over others. Some became so small that they evolved into parasites, tricking other programs into doing the copying for them. The hosts then evolved mechanisms to resist parasites. Some of the host programs were even able to trick the parasites into helping them. Eventually, a form of cooperation emerged where programs helped each other replicate. Then, free-riders emerged who took advantage of this group trust. All of this robust behavior, previously only observed in nature, emerged from Tierra automatically.
Tierra was groundbreaking for the field of Artificial Life, and inspired many systems like it afterwards, including the very robust evolutionary platform, Avida. Most importantly, it gave a demonstration of real evolution occuring in a medium other than nature.
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Anthropomorphize Me
an·thro·po·mor·phize to ascribe human characteristics to things not human. [ref]
“Humans spontaneously imbue the world with social meaning: we see not only emotions and intentional behaviors in humans and other animals, but also anger in the movements of thunderstorms and willful sabotage in crashing computers.” [ref]
The amygdalae are ancient brain structures located deep within the medial temporal lobes of the human brain responsible for quickly processing memories of emotion. Side effects include: tendency to anthropomorphize anything lifelike. The robot, Keepon, developed by Hideki Kozima was built to tap into that part of our brains. Below: Keepon dancing to the Spoon song, “Don’t You Evah.”
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