Category: Cognitive Science

Bats and Belfries

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Thomas Nagel proposes a radical form of skepticism in his new book, Minds and Cosmos, continuing his trajectory through subjective experience and moral realism first began with bats zigging and zagging among the homunculi of dualism reimagined in the form of qualia. The skepticism involves disputing materialistic explanations and proposing, instead, that teleological ones of an unspecified form will likely apply, for how else could his subtitle that paints the “Neo-Darwinian Concept of Nature” as likely false hold true?

Nagel is searching for a non-religious explanation, of course, because just enervating nature through fiat is hardly an explanation at all; any sort of powerful, non-human entelechy could be gaming us and the universe in a non-coherent fashion. But what parameters might support his argument? Since he apparently requires a “significant likelihood” argument to hold sway in support of the origins of life, for instance, we might imagine what kind of thinking could result in highly likely outcomes that begin with inanimate matter and lead to goal-directed behavior while supporting a significant likelihood of that outcome. The parameters might involve the conscious coordination of the events leading towards the emergence of goal-directed life, thus presupposing a consciousness that is not our own. We are back then to our non-human entelechy looming like an alien or like a strange creator deity (which is not desirable to Nagel). We might also consider the possibility that there are properties to the universe itself that result in self-organization and that either we don’t yet know or that we are only beginning to understand. Elliot Sober’s critique suggests that the 2nd Law of Thermodynamics results in what I might call “patterned” behavior while not becoming “goal-directed” per se.… Read the rest

Universal Artificial Social Intelligence

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Continuing to develop the idea that social reasoning adds to Hutter’s Universal Artificial Intelligence model, below is his basic layout for agents and environments:

A few definitions: The Agent (p) is a Turing machine that consists of a working tape and an algorithm that can move the tape left or right, read a symbol from the tape, write a symbol to the tape, and transition through a finite number of internal states as held in a table. That is all that is needed to be a Turing machine and Turing machines can compute like our every day notion of a computer. Formally, there are bounds to what they can compute (for instance, whether any given program consisting of the symbols on the tape will stop at some point or will run forever without stopping (this is the so-called “halting problem“). But it suffices to think of the Turing machine as a general-purpose logical machine in that all of its outputs are determined by a sequence of state changes that follow from the sequence of inputs and transformations expressed in the state table. There is no magic here.

Hutter then couples the agent to a representation of the environment, also expressed by a Turing machine (after all, the environment is likely deterministic), and has the output symbols of the agent consumed by the environment (y) which, in turn, outputs the results of the agent’s interaction with it as a series of rewards (r) and environment signals (x), that are consumed by agent once again.

Where this gets interesting is that the agent is trying to maximize the reward signal which implies that the combined predictive model must convert all the history accumulated at one point in time into an optimal predictor.… Read the rest

Multitudes and the Mathematics of the Individual

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The notion that there is a path from reciprocal altruism to big brains and advanced cognitive capabilities leads us to ask whether we can create “effective” procedures that shed additional light on the suppositions that are involved, and their consequences. Any skepticism about some virulent kind of scientism then gets whisked away by the imposition of a procedure combined with an earnest interest in careful evaluation of the outcomes. That may not be enough, but it is at least a start.

I turn back to Marcus Hutter, Solomonoff, and Chaitin-Kolmogorov at this point.  I’ll be primarily referencing Hutter’s Universal Algorithmic Intelligence (A Top-Down Approach) in what follows. And what follows is an attempt to break down how three separate factors related to intelligence can be explained through mathematical modeling. The first and the second are covered in Hutter’s paper, but the third may represent a new contribution, though perhaps an obvious one without the detail work that is needed to provide good support.

First, then, we start with a core requirement of any goal-seeking mechanism: the ability to predict patterns in the environment external to the mechanism. This is well-covered since Solomonoff in the 60s who formalized the implicit arguments in Kolmogorov algorithmic information theory (AIT), and that were subsequently expanded on by Greg Chaitin. In essence, given a range of possible models represented by bit sequences of computational states, the shortest sequence that predicts the observed data is also the optimal predictor for any future data also produced by the underlying generator function. The shortest sequence is not computable, but we can keep searching for shorter programs and come up with unique optimizations for specific data landscapes. And that should sound familiar because it recapitulates Occam’s Razor and, in a subset of cases, Epicurus’ Principle of Multiple Explanations.… Read the rest

Reciprocity and Abstraction

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Fukuyama’s suggestion is intriguing but needs further development and empirical support before it can be considered more than a hypothesis. To be mildly repetitive, ideology derived from scientific theories should be subject to even more scrutiny than religious-political ideologies if for no other reason than it can be. But in order to drill down into the questions surrounding how reciprocal altruism might enable the evolution of linguistic and mental abstractions, we need to simplify the problems down to basics, then work outward.

So let’s start with reciprocal altruism as a mere mathematical game. The iterated prisoner’s dilemma is a case study: you and a compatriot are accused of a heinous crime and put in separate rooms. If you deny involvement and so does your friend you will each get 3 years prison. If you admit to the crime and so does your friend you will both get 1 year (cooperation behavior). But if you or your co-conspirator deny involvement while fingering the other, one gets to walk free while the other gets 6 years (defection strategy). Joint fingering is equivalent to two denials at 3 years since the evidence is equivocal. What does one do as a “rational actor” in order to minimize penalization? The only solution is to betray your friend while denying involvement (deny, deny, deny): you get either 3 years (assuming he also denies involvement), or you walk (he denies), or he fingers you also which is the same as dual denials at 3 years each. The average years served are 1/3*3 + 1/3*0 + 1/3*3 = 3 years versus 1/2*1 + 1/2*6 = 3.5 years for admitting to the crime.

In other words it doesn’t pay to cooperate.… Read the rest

Science, Pre-science, and Religion

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Francis Fukuyama in The Origins of Political Order: From Prehuman Times to the French Revolution draws a bright line from reciprocal altruism to abstract reasoning, and then through to religious belief:

Game theory…suggests that individuals who interact with one another repeatedly tend to gravitate toward cooperation with those who have shown themselves to be honest and reliable, and shun those who have behaved opportunistically. But to do this effectively, they have to be able to remember each other’s past behavior and to anticipate likely future behavior based on an interpretation of other people’s motives.

Then, language allows transmission of historical patterns (largely gossip in tight-knit social groups) and abstractions about ethical behaviors until, ultimately:

The ability to create mental models and to attribute causality to invisible abstractions is in turn the basis for the emergence of religion.

But this can’t be the end of the line. Insofar as abstract beliefs can attribute repetitive weather patterns to Olympian gods, or consolidate moral reasoning to a monotheistic being, the same mechanisms of abstraction must be the basis for scientific reasoning as well. Either that or the cognitive capacities for linguistic abstraction and game theory are not cross-applicable to scientific thinking, which seems unlikely.

So the irony of assertions that science is just another religion is that they certainly share a similar initial cognitive evolution, while nevertheless diverging in their dependence on faith and supernatural expectations, on the one hand, and channeling the predictive models along empirical contours on the other.… Read the rest

On the Structure of Brian Eno

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I recently came across an ancient document, older than my son, dating to 1994 when I had a brief FAX-based exchange of communiques with Brian Eno, the English eclectic electronic musician and producer of everything from Bowie’s Low through to U2’s Joshua Tree and Jane Siberry. Eno had been pointed at one of my colleague’s efforts (Eric in the FAXes, below) at using models of RNA replication to create music by the editor of Whole Earth Catalog who saw Eric present at an Artificial Life conference. I was doing other, somewhat related work, and Eric allowed me to correspond with Mr. Eno. I did, resulting in a brief round of FAXes (email was fairly new to the non-specialist in 1994).

I later dropped off a copy of a research paper I had written at his London office and he was summoned down from an office/loft and shook his head in the negative about me. I was shown the door by the receptionist.

Below is my last part of the FAX interchange. Due to copyright and privacy concerns, I’ll only show my part of the exchange (and, yes, I misspelled “Britain”). Notably, Brian still talks about the structure of music and art in recent interviews.

… Read the rest

Bostrom on the Hardness of Evolving Intelligence

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At 38,000 feet somewhere above Missouri, returning from a one day trip to Washington D.C., it is easy to take Nick Bostrom’s point that bird flight is not the end-all of what is possible for airborne objects and mechanical contrivances like airplanes in his paper, How Hard is Artificial Intelligence? Evolutionary Arguments and Selection Effects. His efforts to try to bound and distinguish the evolution of intelligence as either Hard or Not-Hard runs up against significant barriers, however. As a practitioner of the art, finding similarities between a purely physical phenomena like flying and something as complex as human intelligence falls flat for me.

But Bostrom is not taking flying as more than a starting point for arguing that there is an engineer-able possibility for intelligence. And that possibility might be bounded by a number of current and foreseeable limitations, not least of which is that computer simulations of evolution require a certain amount of computing power and representational detail in order to be a sufficient simulation. His conclusion is that we may need as much as another 100 years of improvements in computing technology just to get to a point where we might succeed at a massive-scale evolutionary simulation (I’ll leave to the reader to investigate his additional arguments concerning convergent evolution and observer selection effects).

Bostrom dismisses as pessimistic the assumption that a sufficient simulation would, in fact, require a highly detailed emulation of some significant portion of the real environment and the history of organism-environment interactions:

A skeptic might insist that an abstract environment would be inadequate for the evolution of general intelligence, believing instead that the virtual environment would need to closely resemble the actual biological environment in which our ancestors evolved … However, such extreme pessimism seems unlikely to be well founded; it seems unlikely that the best environment for evolving intelligence is one that mimics nature as closely as possible.

… Read the rest

Randomness and Meaning

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The impossibility of the Chinese Room has implications across the board for understanding what meaning means. Mark Walker’s paper “On the Intertranslatability of all Natural Languages” describes how the translation of words and phrases may be achieved:

  1. Through a simple correspondence scheme (word for word)
  2. Through “syntactic” expansion of the languages to accommodate concepts that have no obvious equivalence (“optometrist” => “doctor for eye problems”, etc.)
  3. Through incorporation of foreign words and phrases as “loan words”
  4. Through “semantic” expansion where the foreign word is defined through its coherence within a larger knowledge network.

An example for (4) is the word “lepton” where many languages do not have a corresponding concept and, in fact, the concept is dependent on a bulwark of advanced concepts from particle physics. There may be no way to create a superposition of the meanings of other words using (2) to adequately handle “lepton.”

These problems present again for trying to understand how children acquire meaning in learning a language. As Walker points out, language learning for a second language must involve the same kinds of steps as learning translations, so any simple correspondence theory has to be supplemented.

So how do we make adequate judgments about meanings and so rapidly learn words, often initially with a course granularity but later with increasingly sharp levels of focus? What procedure is required for expanding correspondence theories to operate in larger networks? Methods like Latent Semantic Analysis and Random Indexing show how this can be achieved in ways that are illuminating about human cognition. In each case, the methods provide insights into how relatively simple transformations of terms and their occurrence contexts can be viewed as providing a form of “triangulation” about the meaning of words.… Read the rest

On the Soul-Eyes of Polar Bears

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I sometimes reference a computational linguistics factoid that appears to be now lost in the mists of early DoD Tipster program research: Chinese linguists only agree on the segmentation of texts into words about 80% of the time. We can find some qualitative agreement on the problematic nature of the task, but the 80% is widely smeared out among the references that I can now find. It should be no real surprise, though, because even English with white-space tokenization resists easy characterization of words versus phrases: “New York” and “New York City” are almost words in themselves, though just given white-space tokenization are also phrases. Phrases lift out with common and distinct usage, however, and become more than the sum of their parts; it would be ridiculously noisy to match a search for “York” against “New York” because no one in the modern world attaches semantic significance to the “York” part of the phrase. It exists as a whole and the nature of the parts has dissolved against this wholism.

John Searle’s Chinese Room argument came up again today. My son was waxing, as he does, in a discussion about mathematics and order, and suggested a poverty of our considerations of the world as being purely and completely natural. He meant in the sense of “materialism” and “naturalism” meaning that there are no mystical or magical elements to the world in a metaphysical sense. I argued that there may nonetheless be something that is different and indescribable by simple naturalistic calculi: there may be qualia. It led, in turn, to a qualification of what is unique about the human experience and hence on to Searle’s Chinese Room.

And what happens in the Chinese Room?… Read the rest

Teleology, Chapter 5

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Harry spent most of that summer involved in the Santa Fe Sangre de Cristo Church, first with the church summer camp, then with the youth group. He seemed happy and spent the evenings text messaging with his new friends. I was jealous in a way, but refused to let it show too much. Thursdays he was picked up by the church van and went to watch movies in a recreation center somewhere. I looked out one afternoon as the van arrived and could see Sarah’s bright hair shining through the high back window of the van.

Mom explained that they seemed to be evangelical, meaning that they liked to bring as many new worshippers into the religion as possible through outreach and activities. Harry didn’t talk much about his experiences. He was too much in the thick of things to be concerned with my opinions, I think, and snide comments were brushed aside with a beaming smile and a wave. “You just don’t understand,” Harry would dismissively tell me.

I was reading so much that Mom would often demand that I get out of the house on weekend evenings after she had encountered me splayed on the couch straight through lunch and into the shifting evening sunlight passing through the high windows of our thick-walled adobe. I would walk then, often for hours, snaking up the arroyos towards the mountains, then wend my way back down, traipsing through the thick sand until it was past dinner time.

It was during this time period that I read cyberpunk authors and became intrigued with the idea that someday, one day, perhaps computing machines would “wake up” and start to think on their own.… Read the rest