Posts tagged as “Intelligence”

A while back I mentioned an article Ashwin Ram, Manish Mehta and I wrote on Emotional Memory and Adaptive Personalities:

"Emotional Memory and Adaptive Personalities" reports work on emotional agents supervised by my old professor Ashwin Ram at the Cognitive Computing Lab. He's been working on emotional robotics for over a decade, and it was in his lab that I developed my conviction that emotions serve a functional role in agents, and that to develop an emotional agent you should not start with trying to fake the desired behavior, but instead by analyzing psychological models of emotion and then using those findings to design models for agent control that will produce that behavior "naturally". This paper explains that approach and provides two examples of it in practice: the first was work done by myself on agents that learn from emotional events, and the second was work by Manish Mehta on making the personalities of more agents stay stable even after learning.

Thanks to the good graces of the search engine that starts with a G, I've discussed the article in a bit more depth on their blog in a post titled Maybe your computer just needs a hug.

Please go check it out!
-the Centaur

So a couple days ago I sent off the final draft of a paper on Emotional Memory and Adaptive Personalities to the Handbook of Synthetic Emotions and Sociable Robotics.  Tonight I heard back from the publisher: they have everything that they need, and our paper should be published as part of the Handbook ... in early 2010.

"Emotional Memory and Adaptive Personalities" reports work on emotional agents supervised by my old professor Ashwin Ram at the Cognitive Computing Lab.  He's been working on emotional robotics for over a decade, and it was in his lab that I developed my conviction that emotions serve a functional role in agents, and that to develop an emotional agent you should not start with trying to fake the desired behavior, but instead by analyzing psychological models of emotion and then using those findings to design models for agent control that will produce that behavior "naturally".  This paper explains that approach and provides two examples of it in practice: the first was work done by myself on agents that learn from emotional events, and the second was work by Manish Mehta on making the personalities of more agents stay stable even after learning.

The takehome, however, is that this is the first scientific paper that I've gotten published in the past seven years, and one of the few where I was actually the lead author (though certainly the paper wouldn't have happened without the hard work and guidance of my coauthors).  Here's hoping this is the first of many more!

-the Centaur

So on this last paper ... I spent a year and a half working on the project, six intensive weeks implementing our software doing a crash-course implementation on a testing platform only available for a short time, put the project on hold for a bit during that whole dot-com dancing, and then spent many evenings over the last six months ... and most of the evenings over the last month ... putting together a 10,000 word paper.

End result?  I'm unsatisfied.  I feel like I and my colleagues busted our balls to get this done, and I'm satisfied with the text of the paper qua being a paper ... but scientifically, I think we'd need to put out another 50% more effort to get it up to my standards of what's really "good".  We needed to do many more evaluations (not that we could, as we lost our testbed) but even given that I think the whole paper needed to be more rigorous, more carefully thought out, more in depth.

It's like I had to work my ass off just to get it to the point where I could really see how far I had to go.

Depressing.

-the Centaur

....finished with our chapter submission to the Handbook of Research on Synthetic Emotions and Sociable Robotics.  The book won't come out for another year and a half, AFAIK, but the due date for chapters was yesterday.  Breaking my normal tradition, I'm not going to put up the abstract right now as the chapter is in for blind peer review.  For the past month this has been ... well, you don't want to hear me whine.  But trying to put out a scientific paper at the same time as blogging every day is ... bleah.  Obviously, the paper had to win.

Now, back on track.

Once as a child I asked a Jesuit whether dolphins should be treated like people if they turned out to be intelligent.  I think I phrased it in terms of the question "whether they had souls", but regardless the Jesuit's answer was immediate and clear: yes, they have souls (and, by implication, should be treated like people) if they had two things - intellect and will.  Years later I read enough Aquinas to understand what he meant.  But when I tried to regurgitate my understanding of these concepts for this essay, as partially digested by my thinking on artificial intelligence, I found that what came up were new concepts, and that I no longer cared what Aquinas thought, other than to give him due credit for inspiring my ideas.

So, in my view, the two properties that a sentient being needs to be treated with respect due to other sentients are:

• Intellect: the ability to understand the world in terms of a universal system of conceptual structures


• Will: the ability to select a conceptual description of a desired behavior and to regulate one's behavior to match it

In this view, part of the reason that we treat animals like animals is that their intellects are weak and as a consequence their wills almost nonexistent.  While animals can learn basic concepts and do basic reasoning tasks, it's extraordinarily difficult for them to put what they can learn into larger structures that describe their world - for example, it takes years of intensive training for chimps to learn the basic language competencies a human child gets in eighteen to twenty four months.  Without the ability to put together "universal" structures that describe behavior, your cat can't describe behaviors much more sophisticated than "I'm not allowed in the art studio" and hence is vulnerable to all sorts of hazards and prone to all sorts of misbehavior because they simply can't understand that, for example, it's not a good idea to go out after 2am since their owners won't be awake to let them in.

Similarly, children are wards of their parents because they haven't yet learned the conceptual structures of what they should do, and lack the self-regulation to guide themselves to follow what they have learned.  Violent criminals become wards of the state for the same reason - either they didn't realize that it was a bad idea to hurt their fellow man, or more likely didn't bother to regulate themselves to achieve it.  A similar problem occurs for a variety of neurodiverse people who, for one reason or other, are not able to regulate their behaviors well enough to manage their lives without the assistance of a caregiver (though having various kinds of self-regulatory dysfunctions is not necessarily a sign that someone does not have a sophisticated intellect, and there are a number of autistic people who would argue that we are too quick to discriminate; but I digress).

Regardless, so intellect and will are ideas that bump around in my head a lot.  Can something understand the world it's in in abstract terms, and figure out its relationship to it?  And given that understanding, can it decide what kind of life it should lead, and can it then actually follow that life?  Anything that can do that gets a free pass towards being treated with respect - if you have those fundamental capabilities I'm inclined to treat you like a fellow sentient until and unless you prove me wrong.

We may seem to have gotten pretty far from souls here.  But for the Christians in the audience, think about intellect and will for a moment.  Something that had intellect could learn who Jesus was, and something with will could decide whether or not to follow him.  And it wouldn't matter whether that was a neurotypical person, an autistic person, a talking dolphin or an intelligent machine.  For the atheists in the audience, this may be an easier sell, but the point actually is still the same: something with a truly universal intellect could evaluate a system of beliefs that it was presented, and with a selfregulatory will decide whether or not it was going to agree and/or follow that system of beliefs.

Thinking out loud here...

-the Centaur

Researching another story I came across this tidbit:

Eyewitness Memory is Unreliable
Australian eyewitness expert Donald Thomson appeared on a live TV discussion about the unreliability of eyewitness memory. He was later arrested, placed in a lineup and identified by a victim as the man who had raped her. The police charged Thomson although the rape had occurred at the time he was on TV. They dismissed his alibi that he was in plain view of a TV audience and in the company of the other discussants, including an assistant commissioner of police. The policeman taking his statement sneered, "Yes, I suppose you've got Jesus Christ, and the Queen of England, too." Eventually, the investigators discovered that the rapist had attacked the woman as she was watching TV - the very program on which Thompson had appeared. Authorities eventually cleared Thomson. The woman had confused her rapist's face with the face the she had seen on TV. (quote taken from Baddeley's Your Memory: A User's Guide).

It simply staggers my imagination that someone testifying about unreliable eyewitnesses would then get accused of something by an unreliable witness ... who herself had been watching him talk about unreliable witnesses and got confused!

-Anthony

Who am I?  What do I do?  Why?

I am an artificial intelligence researcher.

I study human and other minds to aid in the design of intelligent machines and emotional robots.

I believe emotions are particularly important for robots because, unlike intelligent machines which normally run as computational processes on a general computer maintained by some other agent, robots have physical bodies with physical needs that they themselves are in part responsible for - and an emotional system's functions are to evaluate how our current situation meets our needs, to trigger quick reactions to get us out of harm, and to motivate us to pursue long-term actions to improve our lot.

I pursue artificial intelligence because right here, right now its techniques help me construct better software artifacts and deepen my understanding of the human condition, and because I hope that creating human level intelligence and beyond will improve the lot of human kind and further the progress of sentient life.

I think these things often, but I never say them.  Time to change that.

-Anthony

Zounds! Even more rogue clones!

Actually,this is from an article on Mixing Memory about how you can get an illusion analogous to the Thatcher illusion with negatives.

Again, these two pairs of faces are the same, except the top two are negatives. The one on the top-left (a) is the pure negative, which Antis describes as being "analogous to an upside-down face." The one on the top-right (b) is negative except for the eyes and teeth, which are positive. This is analogous to the "Thatcherized" face (the one with the inverted mouth and eyes). The bottom two faces were created by reversing the contrast of the top two faces. Thus the bottom-left face (c) is normal, and the bottom-right face (d) is normal except for negative teeth and yes. Now the contrast between the positive face with two negative features makes for a hideous, zombie-like ex-PM (I keep waiting for lightning bolts to come out of his eyes), not unlike the upright Thatcherized face in its grotesqueness. And that's the Tony Blair illusion.

The original Margaret Thatcher illusion is just as startling:

Look at the image below. You will notice some little differences, but they hardly trigger your brain to notice them... but wait! If we flip this same image, you will see the differences are anything, but "unnoticable"!

I'm told the judges would also have accepted "Proof Tony Blair is a Vampire" or "Famous British Politicains Get Possessed" as titles for this post.
-the Centaur

Recently as both a followon to my thesis research and as a part of my work for the Search Engine That Starts With A G, I've been investigating a number of papers on graph theory as applied to semantic networks and Web link graphs. This work isn't "new" per se, since these models and techniques for graph analysis go back years if not decades, but it's only recently - when vast real-world networks have become available in machine-readable form along with the computer power necessary to analyze them - that enough work has been done to illuminate how important it is to analyze the properties of networks in detail.

One of the most interesting papers I've encountered so far was The Structure and Function of Complex Networks, a survey of mathematical and empirical studies of networks that I had wish had been available when I was doing my thesis work. The most important result I think to come out of recent graph theory is that simple uniform and random models of networks don't tell the whole story - now, we have new mathematical tools for modeling a wide range of graph architectures, such as:

• Small World Networks. A traditional graph model says nothing about how far you may need to travel to find an arbitrary node in the graph. Think of square tiles on a floor - each tile is connected to four others, but the number of steps needed to reach any tile is a function of the distance. But anyone who's played the parlor game "Six Degrees of Kevin Bacon" knows that real-world human relationships aren't arranged this way: everyone is connected to everyone else in the world by a very short chain of relationships - on average, you can reach almost anyone in the world in only six or seven handshakes. This shows up in graph analysis as the "mean geodesic distance" between two nodes in a graph, and is an important property we should measure about our networks as they grow to determine what kind of network structure we are really dealing with. At the very least, a random graph structure shows small-world properties more similar to real-world graphs than uniform graphs, and we should consider using them over uniform models as a basis for analyses.
  



• Scale-Free Networks. Both uniform networks - where every node has the same link structure - and random networks - where nodes are connected at random to each other across the graph - have a definite scale or rough average size. Nodes in a random graph are like people: each one is unique, but their heights are distributed over a defnite scale so there are few people shorter than three feet and no people taller than nine. Real world networks don't have this definite scale: instead, they look the "same" no matter what size scale you're looking at. Nodes in a real world graph are like the distribution of city sizes: for every city there are four times as many cities at half that size. This shows up technically in the "degree distribution": the statistical pattern of the number of links on each node. This will no doubt have significant effects on processes operating over networks like spreading activation.
  

There are more issues in graph theory than I can readily summarize, including issues like resilience to deletion, models of growth, and so on; many of which are directly relevant to studies of semantic networks and processes that operate over them.

Another paper, The Large-Scale Structure of Semantic Networks, applies these techniques to real-world semantic network models drawn from sources such as WordNet and Roget's Thesaurus. This paper, like the survey article Graph Theoretic Modeling of Large Scale Semantic Networks, seems to find that real semantic networks have scale-free, small-world properties that aren't found in the simpler mathematical models that people such as Francis (cough) used in his thesis.

SO, anyone interested in semantic networks or spreading activation as a tool for modeling human cognition or as a representation scheme for an intelligent system would do well to follow up on these references and begin an analysis of their systems based on these "new" techniques (many of which have been around for a while, but sadly hadn't reached everyone in the semantic network community (or, at least, hadn't reached me) until more recently.

So check them out!
-the Centaur