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Monday, October 15, 2007

Confabulation Theory

How do we think? How does human cognition work? How can intelligence emanate from a bunch of cells seemingly randomly connected together? Even if the cells (neurons) and their interconnections are carefully arranged, how can that possibly be the basis for thinking?

Dr. Robert Hecht-Nielsen1 is certain he has the answers to all these questions. These answers are contained in his recently released book, Confabulation Theory: The Mechanism of Thought.

There is absolutely no consensus in the neuroscience and artificial intelligence communities supporting Robert's theories. However, seeking consensus is not one of Robert's strong points. As an example, he was a leading proponent of the use of artificial neural networks (as they were called at the time) for various applications even though they had fallen into disfavor amongst most researchers (and funders) after Minsky proved that the popular neural net configurations at the time (called "perceptrons") were incapable of doing something as simple as an "exclusive or" operation:
This was followed in 1962 by the perceptron model, devised by Rosenblatt, which generated much interest because of its ability to solve some simple pattern classification problems. This interest started to fade in 1969 when Minsky and Papert [1969] provided mathematical proofs of the limitations of the perceptron and pointed out its weakness in computation. In particular, it is incapable of solving the classic exclusive-or (XOR) problem...
In my opinion, Minsky's main motivation for "proving" the ineffectiveness of neural networks was that his expertise was in different areas of artificial intelligence research and he wanted to stifle funding of neural net research so that his funding would be increased.

Robert persevered against the prevailing opinion and founded HNC Software in 1986 to develop neural net applications. By the late 1990s, HNC Software had gone public and achieved a market valuation of over a billion dollars because of its neural net applications in many areas such as credit card fraud detection (not to mention good timing relative to the Internet bubble). HNC Software later merged with Fair Isaac to continue as a market leader in these and other areas.

What I've learned is that while Robert's theories are often far-fetched and his certitude regarding those theories is sometimes unwarranted, it's still a bad idea to bet against him.

So what is the Confabulation Theory of cognition? Here's a fairly concise description for the layperson:

Hecht-Nielsen proposed a theory based on four key elements to account for all aspects of cognition. The first hypothesizes that the human cerebral cortex is divided into about 4,000 ‘modules,’ each of which is responsible for describing one ‘attribute’ that an object of the mental universe may possess. An object attribute is described by activating the one ‘symbol’ that is the most apt for that object. (Each module has thousands of symbols, each represented by a collection of about 60 neurons.) “Symbols represent the stable ‘terms of reference’ for describing the objects of the mental universe which clearly must exist if knowledge is to be accumulated over decades,” argued Hecht-Nielsen. “Past theories have avoided such ‘hard’ and ‘discrete’ terms of reference because they seem – but are not – at odds with the widely assumed ‘mushy’ or ‘fuzzy’ qualities of neuronal stimulus response.”

The theory’s second key element is also a hypothesis: that each item of cognitive knowledge takes the form of axonal links between pairs of symbols. These ‘knowledge links,’ the theory posits, are implemented using a two-stage version of the “synfire chain” structure hypothesized by Israeli neuroscientist Moshe Abeles. According to Hecht-Nielsen’s theory, the average human possesses billions of these links – a claim which, if true, would make humans enormously smarter than currently believed by philosophers, psychologists, and educators.

The third foundation of Hecht-Nielsen’s theory is that thinking is divided up into simple, discrete winner-take-all competitions called ‘confabulations.’ Each confabulation is carried out by a cortical module when it receives an externally-supplied ‘thought command’ input. The winner is whichever symbol of the module happens to have the highest level of excitation supplied to the symbols of the module by incoming knowledge links. “The winning symbol is the conclusion of the confabulation, and this simple confabulation operation is believed to happen in less than a tenth of a second,” said Hecht-Nielsen. “It is a widely applicable, general purpose, decision-making procedure, and the theory argues that all aspects of cognition can be carried out by means of a few tens of these confabulation operations per second, many of them in parallel.”

The final element of the UCSD neuroscientist’s Confabulation Theory hypothesizes that every time a confabulation reaches a conclusion, a ‘behavior’ (a set of thought processes and/or movement processes) is instantly launched. “This explains how humans seem to launch many behaviors during each waking moment,” said Hecht-Nielsen. “In other words, every conclusion reached by a confabulation represents a changed state of the mental world, and a behavioral response associated with that changed state is instantly launched.” The associations between each conclusion symbol and its ‘action commands’ are termed ‘skill knowledge,’ which decays rapidly if unused because it is learned by repeated practice trials (since skill learning is managed by a deeply buried part of the brain called the basal ganglia). Cognitive knowledge, on the other hand, is long lasting because knowledge links form in response to meaningful co-occurrence of the involved symbols (an astoundingly prescient idea first advanced by Canadian neuroscientist Donald Hebb over 50 years ago).

Using these elements, explains Hecht-Nielsen, brains can apply millions of relevant knowledge items in parallel to arrive at an optimal conclusion – in less than a tenth of a second. “Confabulation is an alien kind of information processing with no analogue in today’s computer science,” he noted. “Tens of these confabulation operations happen in our minds every waking second, with each conclusion reached launching new behaviors, and this occurs all day long.”
That's all there is to it!

Robert has done a number of very impressive computer simulations to back up his theory. My favorite is the "Plausible Next Sentence" experiment. In this experiment, two sentences are presented to a confabulation architecture consisting of the equivalent of a few hundred million neurons with a potential of around a trillion connections between them. The simulation then confabulates a "Plausible Next Sentence". Here's one example:

Input Sentences: Michelle strengthened from a Category 2 to a Category 4 storm Saturday, with winds reaching 140 mph, but it was expected to weaken before it reached Florida. The storm or its effects could strike the Keys and South Florida tonight or early Monday, said Krissy Williams, a meteorologist at the National Hurricane Center in Miami.

Confabulation Result
Forecasters warned residents to evacuate their homes as a precaution.
The confabulation result is a very reasonable and plausible next sentence. It clearly makes sense within the context of the previous sentences showing that the confabulation "understood" those input sentences. The confabulation result is completely novel - the simulation had never previously seen the result sentence. Other than "to" and "a", not a single word in the result is present in the input sentences. Yet it "knows" that those words make "sense" given the current context.

Also, note that the grammar, capitalization, and punctuation are perfect. This is particularly surprising because in this simulation architectures there are no:
  1. Algorithms
  2. Software routines (beyond the simulations of the functional elements)
  3. Rules
  4. Ontologies
  5. Priors
  6. Bayesian networks
  7. Parsers
From this research, grammar, including capitalization and punctuation, seems to be an emergent property of language comprehension. No effort or mechanism was included to explicitly understand grammar in order to output the resulting sentence.

All knowledge contained within this system was derived from "reading" a corpus containing several billion words representing hundreds of millions of sentences contained in numerous novels, magazine articles, and other reference materials. In this case, "reading" consisted of translating each word and punctuation mark into a unique symbol number (for example, "the" might be symbol number 43,219) and strengthening the simulated axonal connections between symbols in various modules in the confabulation architecture as described above. It took the simulation several weeks to "read" the corpus.

The confabulator needed to "know" an impressive amount for the above example. It "knows" that there are homes in "South Florida" or the "Keys". It "knows" that it could be a good idea to evacuate in the case of storms like this. However, it "knows" that it's only a "precaution" because the storm is "expected" to "weaken". It "knows" that "forecasters" are probably involved and that "authorities" will be the ones to suggest the "evacuation".

In summary, the response was creative, knowledgeable, and intelligent. Anyone below a tenth grade reading comprehension level would be hard pressed to do as well and anyone, regardless of level, would be challenged to do materially better.

This is, by far, the most advanced example of a system based on a brain-like architecture. This is the only example I've seen of creative and intelligent language skills emerging from a massive number of simple connected symbolic elements. In fact, it's the only example I've seen of this level of language understanding by any computer ever. To me, this seems like the beginning of true artificial intelligence.

Here are several more examples from the Plausible Next Sentence experiment. For sure, some of the results are better than others, but in each case, the sentence is plausible and reasonably intelligent. If you take time to think about it, each result shows a remarkable amount of knowledge about the context and about the world given the vast diversity of topics.
Input Sentences: Several other centenarians at Maria Manor had talked about trying to live until 2000, but only Wegner made it. Her niece said that Wegner had always been a character – former glove model , buyer for Macy's, owner of Lydia's Smart Gifts downtown during the 1950s and '60s – and that she was determined to see 2000.

Confabulation Result: She was born in the Bronx Borough of New York City.
Input Sentences: A total of 22 defendants were convicted after the five-month trial of possessing explosives and plotting terrorist acts, but all were acquitted on charges that they were linked to the Al Qaeda terrorist network. Jordanian authorities now have a second chance on the Hijazi case.

Confabulation Result: The defendants are accused of conspiring with the outlawed rebel group.

Input Sentences: The doctrine is frank about Russia's economic weaknesses, calling for efforts to strengthen the economy in order for the country to remain a major power. It acknowledges that it is in Russia's interest to maintain its economic links to the outside world and there is no suggestion that it intends to abandon free market principles.

Confabulation Result: President Boris Yeltsin has expressed his willingness to compromise.

Input Sentences: Investigators say one man who got his license through a fixed test was Ricardo Guzman, the driver of a truck involved in a 1994 wreck in Wisconsin that killed six children in a burning minivan. Prosecutors say Bauer, now retired, hastily shut down the probe of the accident and blocked other investigations that might have embarrassed Ryan.

Confabulation Result: The driver fled the scene after the collision.

Input Sentences: The shortage has been attributed to rapid expansion of the prison system, low pay, a booming economy that makes the prospect of spending the day guarding convicts less attractive, and the risks of dealing with inmates who seem to be getting meaner and more violent. Prison officials are scrambling to keep penitentiaries staffed, recruiting at schools and from the Internet.

Confabulation Result: Prison officials are still debating what they have to do.

Input Sentences: Outside investigators announced the conclusions Tuesday as NASA's top scientist confirmed that the agency will cancel plans to launch a robot spacecraft in 2001 on a mission to land on Mars and indefinitely postpone all future launches to Mars, with one exception: a 2001 mission. With only its aging Mars Global Surveyor in orbit around Mars, the agency is reassessing its entire approach to the exploration of the planet after losing all four of its spacecraft bound for Mars last year – a package totaling $360 million.

Confabulation Result: Mars Global Surveyor will be mapping out the planet.

Input Sentences: Seeing us in a desperate situation, the Lahore airport authorities switched on the runway lights and allowed us to land with barely one to two minutes of fuel left in the aircraft, he said. At Lahore, Pakistani authorities denied Saran's request to accept wounded passengers and women and children, but they refueled the plane.

Confabulation Result: Airport authorities said they were not consulted beforehand.

Input Sentences: People protesting the INS decision gathered today in front of the agency's offices in Miami and the home of relatives who have cared for the boy since he was rescued on Thanksgiving Day . The boy was found clinging to an inner tube at sea after his mother and nine others died when their boat sank during their effort to leave Cuba for Florida.

Confabulation Result: Elian's mother and her grandparents perished in concentration camps.

Input Sentences: But the constant air and artillery attacks that precede the advance of Russian troops have left civilians trapped in southern mountain villages, afraid to venture under the bombs and shells raining on the roads, Chechen officials and civilians said. Residents of the capital Grozny who had fled the city in hopes of escaping to Georgia, which borders Chechnya to the south, have been stuck in the villages of Itum-Kale, 50 miles south of Grozny, and Shatoi, 35 miles south of Grozny.

Confabulation Result: Russian forces pounded the strongholds in the breakaway republic.

Input Sentences: The National Corn Growers Association says Gore is likely to have an ear of corn following him too if EPA sides with California officials, who oppose using ethanol. Ten days before the Iowa caucuses, Gore was more than 20 points ahead of Bradley in various Iowa presidential polls.

Confabulation Result: Gore's aides said they would not have any problems.

Input Sentences: The incident threatens relations between the Americans and Kosovo civilians, whom the peacekeepers were sent to protect after the 78-day NATO bombing campaign. We don't want them here to give us security if they are going to do this, said Muharram Samakova, a neighbor of the girl's family.

Confabulation Result: NATO has struck a military airfield near Pale.

Input Sentences: Now, I must admit that I'm not so sure the Palestinians really wanted to reach a framework agreement, Eran said Tuesday. Eran wondered aloud whether the Palestinian strategy might be to negotiate as much land as possible in the remaining transfers, then declare statehood unilaterally – as the Palestinians have threatened to do before when talks bog down.

Confabulation Result: Netanyahu said the Palestinians would be barred from jobs in Israel.
Ultimately, as impressed as I am with this research, I can't recommend Robert's book. It's a mish-mash of presentation slides and Robert's research papers which, since research is incremental, are rather repetitive. Also, links to all the papers and presentation are available for free from Robert's website if you're interested in more of the details.

Robert addresses why his theory hadn't been already discovered and embraced. Here's his answer from the book:
Since the mathematics of confabulation is simple, an obvious question is "Why wasn't confabulation theory discovered long ago?" A key reason is a decades-long intellectual constipation brought about by what might be called the "Bayesian religion."
Well, Robert, tell us how you really feel about other researchers! Robert's definitely not the most political or consensus oriented guy that ever lived, but he's quite a confabulator. And quite a humorist too (though not intentionally) - I laughed out loud when I read the above quote.


1Full disclosure: Robert is a friend of mine, and yes, I am very biased regarding this particular topic so the reader should significantly discount everything in this post.


Bret said...

This post is related to "Soul or No Soul?" at The Daily Duck. In particular, the claim for "Soul" is partly based on the following: "There is no clear scientific consensus on how the brain produces the higher functions we call being human."

That's true, but Hecht-Nielsen has demonstrated a pretty high level of cognition with his theories and experiments, even given that there's no consensus. It doesn't take a whole lot of imagination to see that quite a lot of intelligence can emerge from simple (though massive) networks of neurons.

This "gap" that God fits into is likely to get much smaller in the near future.

Yet, at the same time, another gap will remain forever - the quantum gap. The brain has so many components operating at the molecular level that quantum effects make a difference. God can always be posited to inhabit those gaps and it will never be provable one way or the other. Free will, if it exists, could always exist in that gap as well.

Hey Skipper said...


Free will, if it exists, could always exist in that gap as well.

Since we can never rewind Time's tape, we could never come close to proving free will does not exist, even if it is objectively true that it does not.

Bret said...

True, but even if you could rewind Time's tape, it wouldn't replay exactly due to quantum effects. Of course, the whole universe is susceptible, not just brains.

yaxu said...

These are impressive examples, but is it made clear anywhere how typical they are of the general output from the confabulator? Are they picked at random or chosen as the best examples from a large number of less-good outputs?

It would be interesting as least to see what happens when the confabulation goes wrong, comparing them to human speech errors and so on.

Bret said...


Sometimes the confabulator won't return a result. This is certainly true if you type in gibberish as the input sentences or if it hasn't seen the words in the input sentences (making it gibberish to it).

When it returns a result, my understanding is that the sentence is always well formed. Sometimes the results makes more sense than others, just like the example listed. However, to someone who knows nothing about the input sentences, the result always seems plausible.