Cognitive Science 366

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2009-10-27T13:32:00.001-07:00

Semantic Halos

2009-10-25T17:00:00.000-07:00

Hofstadter starts by stating that the foundations to perceiving patterns and ascribing rules about those patterns lie in the ability to recognize analogies and abstract resemblances. He continues into an analogy problem between American and English government structure, which leads into conceptual halos of words and concepts.

One concept or word has numerous meanings, each of which can fall across many different contexts. These concepts/words are not merely one idea but are composed of multiple ideas and are linked with other concepts, words, meanings, and ideas. In Hofstadter's example of English and German concepts for hard he concludes that context and culture play a huge role in determining the boundary of concepts. Ideas about language apply only in the context of the language being discussed. The concept denoted by hard in English or by schwer in German are not universal, but instead apply only in each language and are quite different when compared to another language or considered in another language.

This reminded me of a question I had about conceptual spheres after a discussion with my boyfriend on a topic we briefly discussed in class: chairs. His conceptual sphere of what constitutes a chair differed from mine, which led me to believe concepts cannot be concrete if what we associate with that concept or consider that concept to entail is not universal by any means. Professor Graci briefly mentioned an exhibit he attended in which there was a room filled with assorted chairs; I believe he said if it had not been noted beforehand one may not have known that each object was a chair. As I told my boyfriend about this he insisted that the majority of these could not have been chairs, especially if they did not fit into certain requirements which he gave me.
1) A person must be able to sit on or in it
2) It must raise one from the ground
3) It must have some sort of back support
...and I believe the list went on but my head began to slip into wondering why certain things would fit into my concept of "chair", which was pretty flexible, but they would not fit into his rigid concept of "chair". For instance, he would not consider a stool to be a chair, whereas I would. He would not consider an object to be a chair any longer if the legs were cut off and it were placed on the ground, whereas I would. I had an extremely loose concept of what a chair could be, simply an object made to be sat upon, a category to which other objects fall into (e.g. booth, stool, sofa, etc). We discussed the requirements for a computer to recognize a chair, and concluded that we both associated objects outside of the computer's conceptual sphere (e.g. a chair on the ceiling as mentioned by a fellow classmate when Professor brought up the exhibit). However, we could not come to a conclusion as to what fit into the conceptual sphere of "chair"; we simply could not agree on a rigid definition or idea. Once again, this led me to wonder how there could be stark differences in the idea of what constitutes or pertains to certain concepts.

"conceptual slippage" = "context-dependent tolerance of conceptual mismatch."

BACON

2009-10-25T16:04:00.000-07:00

Chapter Four illuminates the argument presented in Preface Four, which stated that computer technology is not capable, or even near being capable of, human cognition. The omission of information, exaggeration, or misleading explanations of capabilities of computer programs, so that it is believed they are able to use some aspect of human cognition is called the Eliza Effect. Chapter Four goes further into detail on such misleading stories of computers and perception. In one case a program titled BACON is said by its developers to be able to deduct universal laws from "original data". It turns out the program is given all the data necessary to discover the laws; data and information that may not have been available or possible to know at the time of their original discovery. Chalmers et al. states that "[t]he program was given precisely the set of variables it needed from the outset (even if the values of some of these variables were sometimes less than idea), and was moreover supplied with precisely the right biases to induce the algebraic form of the laws, it being taken completely for granted that mathematical laws of a type now recognized by physicists as standard were the desired outcome." (p 178) This is a prime example of the problem with all computers in perception. It is necessary to give the information to the computer beforehand in which it can deduce the answer from. No program runs on knowledge that is not supplied. It can assign new variables but it has to have been told in advance some new variables will be creased that it will have to assign some variable to, it has no autonomy in the matter. It cannot think on its own. It needs a programer who has supplied the information necessary.

Although this does make me question the point of Hofstadter's programs at all. His work focuses on mimicking human cognition with his programs, yet even when the computer finds, for instance, underlying patterns by using methods similar to human cognition, the computer is not aware. Descartes, James, and many others would say that without being aware of oneself and cognition nothing more can exist besides an inanimate object. However, by modeling human cognition with Hofstadter's programs we may be able to better understand the functioning behind cognition. Maybe it is not Hofstadter's goal to create a self-aware computer, but just a computer which models some aspects of human cognition.

Eliza Effect

2009-10-22T14:12:00.000-07:00

So I was I was buddies with Hofstadter so I could recommend this great movie to him and chat him up about misconceptions about artificial intelligence, specifically the Eliza Effect, which he discusses in Preface 4. I just watched this great movie, The Surrogates (which the worst aspect of the movie was the leading character, Bruce Willis). It is the first movie I have watched about computers in the future where it didn't focus on the intelligence, or human-like capabilities in thought of computers. There was no jumping from modern technology to a future of computers who completely understood concepts and could think like a human; it did not question the morality of artificial intelligence. There was no good versus bad computers, it was all about brain-computer interaction. The machines did not understand concepts or think on their own, they simply moved and obeyed commands from their human counterpart.
Point of it all, it was refreshing to see a movie about computers of the future which did not focus on computers that are just as capable in thought as human, considering we are far from making computers understand the most, trivial to humans, but complex facts for computers. As we discussed in class, computers cannot identify a chair in the conceptual sphere that a human can. When thinking about possibilities for computer intelligence, humans quite often forget about how much knowledge goes behind the simplest concepts, how much background knowledge it takes to read and understand a paragraph. For instance, in Hofstadter's preface, philosopher Margaret Boden refers to a program "ACME" which is supposed to be able to understand Socrates' analogy between philosopher's(as teachers) and midwifes. The program seems to have no understanding of any of the words which are being presented, it simply follows a pattern which is given to it in two instances. It has no clue about the differences between variables, they could be synonyms or antonyms for one another. The program simply plugs the variables into a given formula without understanding any relationship between midwives and philosophers, or that it is even dealing with substantially different terms, it does not even know they are made of a different string of characters (the program compares them and receives the information that these strings are not the same, but it does not actually know or learn). Hofstadter goes on to show this with his example of how a relationship between a completely irrelevant story could be drawn to resemble what the program supposedly understood. I completely understand why Hofstadter was so upset about the misconceptions that the Eliza Effect causes, it is why we have so many bad AI movies about the morality of computers in the future.

Math Methods

2009-10-06T20:15:00.000-07:00

The sample run of Numbo illuminates Numbo's attempt at modeling human cognition. The program uses the same methods that most humans use when trying to solve a problem as well as the declaritive knowledge stored in the Pnet. Some of these methods were described earlier in the chapter. I thought about how useful these techniques really were and decided that they are little methods I don't even realize I use because it happens so fast; I only notice when they don't work because then it gets more difficult and I have to really concentrate on the problem. I think Hofstadter says something to that effect about Jumbo...but anyways as I was looking through my materials that are supposed to prepare me for the math section of the GREs I realized that I use these methods, just mostly in some what of an unconscious or mechanical way. I like that Numbo puts these human methods to use, especially the knowledge of approximate sizes of numbers and rote small-number arithmetic. I think a lot of knowledge can be derived from using these simple methods, to build a more complex idea to solve a problem.
In Defays' second to last paragraph he articulates the capabilities and possibilities of Numbo as a program attempting to emulate human cognition, or at least be a step further in that direction.
"The Numbo project has shown that, with an appropriate architecture, a system can behave, at least in a limited domain, in a very fluid, humanlike way, combining the ability to spontaneously perceive chunks, the ability to manufacture groups, and the ability to achieve goals through the chaining of different operations. Of course, Numbo's capabilities could be greatly imporoved."

Seeds of the Mental

2009-10-04T16:50:00.000-07:00

Daniel Defays' paper discusses the number problem Numbo, similar to Jumbo, a slightly different form of Crypto. Numbo attempts to simulate human cognition, namely pattern recognition. Solving Numbo and Crypto with a program are both good models of human cognition, with Crypto being slightly simpler, considering there are less possibilities due to more rules. Numbo's Pnet seems particularily complicated; I feel like much of the knowledge stored in the human brain is not easily brought to the surface when trying to think of relationships between numbers that we call upon to help solve problems such as Numbo or Crypto. It would prove difficult to capture every connection we might make between numbers to solve a problem; as the paper says, knowledge of relationships between numbers varies from one individual to the next. The knowledge used may differ each time as well, as the preface says. Depending on the context we may draw on a different method to figure out the relationship between bricks and the target. It would be quite a complicated system, that would constantly be changing, to store "common knowledge" of relationships between numbers.
I did, however, like the idea of giving links weights and nodes different degrees of activation. This reminded me of neurons in the brain. Not only does there seem to be a degree of plasticity in this idea of degrees of activation and weights but it also seems to communicate much like neurons in the brain. The nodes communicate by activation spreading throughout the nodes in an uniform pattern (okay so it differs slightly from the brain, but it is the idea of activation spreading from one node or neuron to its neighbors that resembles human cognition). I kind of saw something similar to plasticity in the way that Defays descripes how due to the context and other intrinsic factors, some nodes or links will be more prone to activation than others. This vaguely reminds me of plasticity or how some pathways in the brain that are activated more than the surrounding areas have stronger connections. I love that Defays thought this vital to his program, and I agree it is integral in modeling human cognition, for the functioning to resemble is as closely as possible.
Numbo also seems to have something similar to the "commonsense halo". Defays says that "[a]ssociation (simulated by spreading activation) is clearly the key notion here -- but total reliance on blindly spreading activation can give rise to uncontrolled, chaotic behaviors of the network." Therefore, some system must be implemented to keep the program in the "commonsense halo" of relationships of the numbers it is working with. As we have learned, this is also similar to human cognition; the "commonsense halo" keeps our cognition on track and from drifting from one relevant topic to another completely irrelevant topic.
Overall, I enjoyed Defays' paper and Numbo. I do like Crypto more, probably because it is something hands on in class for us to try ourselves, but does Numbo seem to be the basis of our project.

Multiple Musings

2009-09-29T16:31:00.000-07:00

I like Hofstadter's two ideas of ways to transform pseudo-words by using entropy-preserving and entropy-increasing. This reminded me of the word scramble game I play. I use these techniques of regrouping, rearrangement, and disbanding. I use the scramble feature to rearrange the letters, or if I create one word I use regrouping to see what else can be made. When I run out of words to create I start disbanding and then working with what is left. I think regrouping could be improved by the rules that would be given to jumble, so as to prevent the unacceptable initial consonant clustering, as seen in the first paragraph in Hofstadter's 'Entropy-preserving Transformations' section. But then again there might be too many irregular rules in English for Jumble to actually follow any. Such as the single/double syllable problem of "soap", "boa", and "coop".
I think some of the methods that Hofstadter presents would prove useful though because they resemble human cognition. I think that spoonerism, forkerism, kniferism, exchange, and reversal all definitely coincide with human cognition. These are all techniques I think that I use when playing a word scramble game.
So many of the different options for scrambling the letters to pseudo-words in jumble, may yield results in a minuscule amount of instances. How would jumble discriminate when to use each method? Jumble should first use the methods that are most similar to human cognition, then these others. I think human cognition has adapted to recognize or create words, so we are mildly decent at it through these methods.

Jumbled II

2009-09-20T13:43:00.000-07:00

"...everything of interest in cognition takes place above the 100-millisecond level, which he characterizes as the time it takes for you to recognize your mother..."

Initially, I wanted to toy with the idea presented in the quote above but then I read the rest of the section and felt guilty about my previous post. Once again, Hofstadter sets me up to believe he is running with an idea one way, and then he surprises me. In Romances among the Letters, Hofstadter illuminates the connection between letters to create codelets, that bond into gloms that "spark together" to create larger gloms. He illuminates the phenomena of parallel processing by explaining how many items can "spark together" at once or there can many numerous processes going on at once all at different stages of the process. He proceeds to discuss how not only are there parallel bondings occurring but that "parallel exploration" can occur too, where numerous bonds can be made using one structure or letter. The analogy of romances developing parallel but then needing a commitment to proceed into a true relationship is wonderful. He states that it is the same with the letters, eventually bonding and glomming must occur after mates have been tried, compared, and explored. I think this idea captures the essence of how we see words as a whole and are capable of processing jumbled letters into words.

All Jumbled

2009-09-20T13:42:00.000-07:00

I don't like Hostadter's idea in Letters Go Up, Words Come Down, that each time you look at the jumbled letters your mind just randomly mixes the, each time attempting to create a word. I feel like it is extremely hard to do anything randomly in the head. It might just be the imagery he puts into my head. I like his idea of sitting back and kind of "watching" the process that goes on when you cannot figure a combination out that creates a word instantly. I just feel like when I have to sit and think about what words I can create it is not so random, but my head just kind of plays with the vowels and sounds of the consonants. But it might just be me who uses sound to figure out these jumbled letters. I guess when he uses the phrase "toss them in the air" he is referring to a process that is not understood, the same process that just randomly sees a word in the jumbled letters, it does seem random that they are presented jumbled but just pop up unscrambled. I would not phrase it quite the same way as Hofstadter though. I feel as if instead of just randomly jumbling the letters each time I work off connections. Like when he presents the example "ucilgars", my mind instantly sees "cigars" which leaves "ul", then my mind breaks that down into "cars", it doesn't randomly generate a combination of letters to try to derive a word from, but instead works from each word. I feel like this is similar to Hofstadter's pattern finding depth-first strategy. I create one word which I work from to create other words, and when I run out of that little chunk I go back to the initial jumbled list and see if there is another word that I can start to work from. Of course, this might be less efficient than Hofstadter's technique, and considering the man's brilliance I would bet that his would be more reliable or at least would produce more than my technique. Still, I stand by that I am not sure his imagery quite explains what he is implying about how the mind works. However, I did like To Read, or Toreador because I feel like it works for the jumbled letters as well. After much conditioning in grammar school, my mind knows what letters can be chunked, and especially what letters are usually chunked together. So I feel like I naturally pull those chunks out and methodologically place the vowels in between. I would really like to see someone pick up Hofstadter's Toreador project and see what comes of it.

6 Clicks to Jesus

2009-09-16T13:03:00.000-07:00

Hofstadter's sections on conceptual spheres starts out by explaining the commonsense halo or implicit counterfactual sphere. He states that surrounding every event are numerous related variants of the event. He provides three examples: a collapsed bridge, a stabbed female tennis player, and Tylenol murders. in reaction to a bridge collapsing after complaints about its safety, a governor attempts to reconcile by having all similar bridges inspected, which then could have spread out to other states feeling it necessary to do the same. This has a pretty reasonable commonsense halo. Sure, having all the bridges inspected after the fact really does nothing for those who were victims, but it has preventive potential for the future.
The stabbing of a tennis player lead to fear for all female tennis players. This is less rational, taking preventive measures probably is not necessary, and it is definitely out of the realm of the commonsense halo for any entertainer to fear for their safety, more than usual of course or without valid reasons. Then Hofstadter shows how far out of the commonsense halo one can go with the Tylenol murders example. If there were no commonsense halo, which may vary slightly from person to person, then the world would be much too cautious. We could barely life without all the preventive measures and laws that would be enacted to prevent something or another because something happened. Due to this commonsense halo, it just doesn't seem reasonable to jump to such conclusions because of the slightest relativity.
Seems to me like this is a pretty necessary mechanism in the human mind. But what if it was not an important mechanism of the mind, or what if we had really poor commonsense halos? Maybe those Tylenol murders can be connected to random spiking of washing machines on railroads, which can be connected to evil deeds in general, which can be connected to it's opposite: good deeds! Well, this then you could connect to the Bible which is supposed to teach morals and other things, which then you can connect to JESUS, who performed good deeds! Then we would all be like Wikipedia and the numerous links in each article from which you can go anywhere. My boyfriend plays this game, 6 Clicks to Jesus, on Wikipedia. The point is that almost anything can be connected to almost everything! And it just takes 6 Clicks to get that completely irrelevant connection that is somehow relevant.
This conceptual sphere, or commonsense halo, is vital otherwise regulations would be too general (e.g. Well, someone spiked Tylenol, let's enforce strict regulations on EVERYTHING!!!!) or too specific (e.g. Hm, one time someone used a 9mm and a 12-gauge shotgun in a school shooting, let's completey ban those guns. Completely unreasonable because it leaves out so much. Not to say anything about my personal view on firearms.), you cannot predict behavior of all mankind, so going too far out of the commonsense halo would not be beneficial in the long run and not having any conceptual sphere would leave us lacking any preventive measures.

Esthetics

2009-09-14T14:56:00.000-07:00

Hofstadter suggests that esthetics are an integral part of recognizing patterns in math. Certain patterns grab attention because of a collective sense of esthetics. Connections made between numbers may differ according to there knowledge of math or previous experiences with numbers. Unless collective notions of esthetics includes these influences, or these influences affect the collective sense of esthetics then the idea that it is the driving factor behind pattern finding may be slightly skewed. Prior experiences should be included in Hofstadter's conclusion of how patterns are found. I don't think that the community has a collective sense of beauty or of pattern finding. Maybe we all see certain patterns easier but due to our math backgrounds or other things that might affect our ability in seeing patterns I think our sense of the esthetics in numbers are different.
I do like how Hofstadter explains how mathematicians, just like composers, flesh out and develop a new idea by first playing with what all can be done with the idea. I do think it is important to be concerned with proving the result as well, but I like the idea of first questioning how interesting the idea is and what other interesting things can be done with it. I like the idea of eliciting patterns from patterns that are newly discovered themselves.

Math and Music

2009-09-14T13:06:00.001-07:00

In the section Good-bye, Math...Hello, Music! Hofstadter exchanges his examples of patterns in math for music. Hofstadter points out the different elements of music which play "different functional roles", in his example, the note C can occur several times but has multiple functions to influence the elements of the song to create diverse patterns. Just like in the number sequences the music has numerous patterns that can be found behind the overall sound, and can be even more complicated by changing some variables while others are constant. Even with the various elements present in music it is still perceived, for the most part, as a single song. A song is a single structure composed of elements which make a hierarchical build-up. The foundation this heirarchical build-up provides allows for pattern prediction , as with the number sequences.
Hofstadter suggests the variability in music provides ambiguity and context-dependence that are central to the meaning. He then states modeling the perceptions of patterns in music may provide insight into esthetic cognition. Just as pattern finding in math can contribute to understanding processes of the mind, the patterns in music, which may come more naturally to find with the ear rather than number patterns which may take more brain power, can as well.

Side note:
This reading reminded me of the Clay projects in Cognitive Science 266 where we used commands to manipulate various notes or chunks of notes and created a pattern of notes through programming.

Patterns in numbers

2009-09-03T15:17:00.000-07:00

Chapter One: To Seek Whence Cometh a Sequence
Pages: 1-35

This section of the reading focused on the underlying patterns of number sequences. By using a top-down approach to determine basic patterns in a number sequence, the basic pattern can predict a parent number sequence. Programmers are able to provide a computer with the basic pattern to use in a bottom-up fashion to recreate the number sequences.

When I first began reading the chapter I was extremely interested in Hofstadter's illumination of patterns behind well-known number sequences, such as squares. Then after I started to think about it I thought, as interesting as these patterns are that they are quite useless to humans. I was unsure what Hofstadter was implying we should do with these patterns. Then Hofstadter pointed out that this is very different from the way humans thought. Suddenly, it became apparent that he was using a type of top-down approach to model a computer program after human thinking. As Hofstadter states, intelligence is not simply knowledge, so he could not try to teach the computer about all the different number sequences, he had to create a system for figuring out the number sequences by examining the underlying patterns so that the computer could use a bottom-up approach to determine a number sequence.