Agent Plus Environment

Not your everyday summer job

This summer, I’ve been working for NASA as an intern in the Langley Aerospace Research Summer Scholars Program. In a one-sentence summary, I’m working with a systems engineering team to develop and integrate the software and hardware needed for both indoor and outdoor tests of autonomous, unmanned multi-vehicle flight control.

But what does that mean, in terms of what I actually do?

It means the past seven weeks have been spent laboring over keyboards, switching between C, C++, Java, and Processing. I’ve carried my lab’s miniature Parking Lot Exploration Rover outside in 105ºF weather to test a navigation algorithm. I’ve learned about PID controls, GPS sensors, and radio communication. I’ve evaluated ground control station software, delved into the depths of an open source flight simulator, and discovered how tricky network protocols can be. I’ve written software for 3D data display programs, data parsers, and communication links. I’ve learned that when you’re one of a team of ten interns, all tackling pieces of the same large project, communication is crucial.

I’m enjoying this internship immensely. Vassar News just released an ego-boosting article about me and my summer, which I suggest you check out.

You’ll be hearing more from me on this subject. Stay tuned.

Emotional intensity and the individual

Let’s say you’re at home. Maybe you’re lounging indolently on the couch, feet up on the brown wood coffee table, television whining at you from across the room. Maybe you’re cooking tonight’s dinner, chopping vegetables with careful strokes, sliding the ever growing pile of peppers and onions and tomatoes into a hissing frying pan. Maybe not. Maybe you’re in another room when the fire alarm sounds, bleep bleep bleep, blaring its cacophonous melody into your generally peaceful home.

How do you react?

Do you scream? Do you calmly turn off the stove, flap a towel at the cloudy air around the smoke detector, and wait patiently for it to detect that there’s not actually a fire? Do you leap up from the couch, tripping over the coffee table in your panic, terrified of burning to death in your own living room?

The strength of your emotional response to this (or any) emotional stimulus is known as emotional intensity. Emotional intensity can be measured with psychological scales, such as the aptly-named Emotional Intensity Scale (EIS) developed by Bachorowski & Braaten (1994) [PDF]. The underlying if obvious assumptions of these scales are that some individuals experience all of their emotions more intensely than other individuals, and all individuals may respond with different strengths to the same stimuli.

Your personality influences your experience of emotions

You may already be familiar with the Big 5 personality factors: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism (sometimes called Emotional Stability). (If not, look them up.) Robert McFatter, in his 1998 paper Emotional Intensity: Some components and their relations to extraversion and neuroticism [PDF], investigated the relation between temperament and the intensity of positive and negative emotions. (Positive emotions included happiness and pleasure; negative emotions included worry, guilt, anger, and sadness.) McFatter described and tested several models, all of which had slightly different predictions about how neuroticism, extraversion, and positive and negative emotional intensity are correlated.

1. Larsen & Ketelaar model: The measures used to examine emotional intensity in this model tapped frequency of experienced emotions more than the intensity of single (and possibly infrequent) reactions. The model predicts that Extraversion is positively related to positive intensity and unrelated to negative intensity, and that Neuroticism is unrelated to positive intensity and positively related to negative intensity.
2. Larsen & Diener model: This model draws on the theory that the intensity of experienced emotions is used to regulate arousal levels. Arousal level can be tied to Extraversion, so this model predicts that Extraversion is positively related to both positive and negative intensity. Larsen & Diener also predict that Neuroticism is similarly positively correlated with positive and negative intensity.
3. Wallace, Bachorowski, & Newman (WBN) model: Extraversion is suggested to reflect a behavioral approach system and a behavioral inhibition system. Neuroticism is suggested to reflect the reactivity of an arousal system responding to the behavioral approach/inhibition systems that serves to prepare the individual to respond. This model accordingly predicts that Extraversion is positively related to positive intensity and negative related to negative intensity (and thus that Extraversion is overall uncorrelated with overall emotional intensity), and that Neuroticism is positively related to both positive and negative intensity.
4. Gray’s model: This model predicts that the behavioral approach/inhibition systems form dimensions that are rotated roughly thirty degrees from the Extroversion and Neuroticism dimensions, so they don’t line up. The model predicts that Extraversion is positively related to positive intensity but only weakly negatively related to negative intensity. Similarly, Neuroticism is predicted to be weakly positively related to positive intensity, and positively related to negative intensity. Gray’s model, furthermore, suggests that the negative emotions can be subdivided into anger/panic and anxiety/fear categories. These subcategories may have different relations to Extraversion.

Methods, Correlations, Analyses, Results

To test these models, McFatter gave a series of questionnaires to 1553 college students taking introductory psychology classes (596 male). Participants completed the 30-item EIS to examine positive and negative emotional intensity (14 items and 16 items, respectively), the Eysenck Personality Inventory (EPI) for measuring Extraversion and Neuroticism (in addition to subscales for impulsivity and sociability), and a third unrelated questionnaire.

Based on an initial factor analysis of the EIS, negative intensity was separated into two groups: anger/frustration (hereafter referred to as “anger intensity”) and non-anger, such as worry, guilt, and sadness (referred to as “non-anger intensity”). This result supports Gray’s theory that two separate negative emotion systems exist.

Consistent with both Gray’s model and the WBN model, Extraversion was shown to be positively related to positive emotional intensity (r=0.19, P<0.0001), negatively related to non-anger emotional intensity (r=0.18, p<0.0001), and unrelated to anger intensity (r=0.02). In plainer terms, individuals with high Extroversion scores tended to experience more intense positive emotions and less intense negative emotions.

Neuroticism, on the other hand, was shown to be positively related to all three kinds of emotional intensity, though less strongly to positive intensity (r=0.18, p<0.0001) than to non-anger or anger intensity (r=0.56,p<0.0001 and r=0.45,p<0.0001, respectively). That is to say, individuals with high Neuroticism scores tended to report experiencing more intense emotions overall. This is consistent with Gray's model.

A couple other interesting results:

Females reported significantly higher emotional intensity than males overall, with the largest difference seen in negative intensity (0.411, p<0.0001).

The positive relation between Extraversion and emotional intensity was stronger among people with a high Neuroticism score.

Neuroticism and emotional intensity

It’s hard to tell without reading a pile of psychology papers, but the fact that Neuroticism was positively related to positive emotional intensity was surprising. Previous results found a negative relation, though several of these had measured emotional intensity with a different scale–one that seemed to confound frequency and intensity of the experienced emotions. The WBN model, relatedly, claimed that Neuroticism reflected general emotional reactivity. (Recall the personality factor’s other name: Emotional Stability.) So McFatter investigated.

He found that when looking at the difference of the positive intensity and negative intensity scores, the relative emotional intensity was negatively related to Neuroticism, as in those previous studies. However, when examined on their own with the other variables controlled, the relations of both positive and negative intensity to Neuroticism were positive. The WBN model only explained a portion of the story.

McFatter’s results, overall, support Gray’s model and the WBN model, suggesting that the variations in positive and negative emotional intensity may be the result of separate emotion systems, but that they do have some common variation that may best be explained by their relations to Neuroticism.

References:
McFatter, R. (1998). Emotional Intensity: Some components and their relations to extraversion and neuroticism. Person. individ. Diff., 24(6): 747-758. [PDF]

Unresolved

I’m not one to make New Year’s resolutions.

I mean, sure, I could take my pick of popular New Year’s resolutions; I could decide, on the first day of the new year, that this year, I’ll start exercising more and eating better, or that I’ll spend more time with my family and friends, or that I’ll learn a new skill. And if I chose to make resolutions, I’d be far from alone–a 2008 survey on Dorthy.com found that 66% of the 2000+ adults polled had made resolutions at some point (though only 17% managed to keep them).

Making resolutions: It’s about self-control

The question Anirban Mukhopadhyay of the Hong Kong University and Gita Venkatarmani Johar of the Graduate School of Business at Columbia University asked is this: What determines how many goals a person will set, and how successful a person will be at achieving those goals? They performed a few studies in 2005 to look at the relationship between self-control, goal setting, and goal achievement. They suggested that what you believe about self-control affects the goals you set and achieve [PDF].

In the paper, “self-control” is used to mean a sense of willpower. Mukhopadhyay & Venkatarmani discuss various lay theories of self-control, noting that the amount of self-control a person has can be seen as either an inherently limited or unlimited resource, and that this resource can be seen either as malleable or as fixed (the amount of self-control a person has can change over time, or not). An important premise to note here is the idea that the probability of choosing a goal or making a resolution increases if a person thinks that goal can be attained. So if you think you’ll be able to achieve a goal, you’re more likely to set it. Combine this with theories of self-control, and in general, if you believe you have unlimited stores of self-control, you’ll set a larger number of goals. If you believe self-control is malleable but limited, you’ll set fewer goals.

Mukhopadhyay & Venkatarmani also discuss self-efficacy: belief in one’s capabilities, the perceived ability to carry out a desired action. They propose that people with high self-efficacy–people who believe that failure is the result of insufficient effort, and thus exhibit increased commitment and persistence–will achieve more of their goals than people with low self-efficacy, who tend to view failure as the result of deficient ability, and thus may simply give up.

The studies

In the first study, 85 participants (all college students) each read one of four passages presenting lay theories of self-control. Each passage contained two paragraphs; the first discussed self-control either as limited or as unlimited, and the second discussed self-control as either malleable or fixed. The participants then answered questions about their belief in each of two theories presented, followed by a second questionnaire to assess motivation, in which they listed all their current goals.

The study was testing whether a belief in unlimited, malleable self-control would result in most resolutions, and indeed, this is what was found. The experimenters had some concerns about participants’ natural beliefs in relation to the passages they read, however, so in study two, the order of the two measures (lay theories and motivation/goal listing) was varied. Data from 130 new participants revealed that, as hypothesized, if the motivation & goals questionnaire were assessed first, then among the people who believed self-control is malleable, those who also believed self-control to be unlimited (vs. limited) set more goals. When lay theories were assessed first, this result reversed. The people who believed that self-control is fixed were unaffected by order.

The third study moved on to examine goal achievement, adding a measure to look at self-efficacy. The study had two sessions, in November then February. In the first session , the 159 participants read passages about lay theories (much like in study one, but with longer passages to strengthen the manipulation), listed the resolutions they were planning on making at New Years, rated how disappointed they would be if they failed to keep their resolutions, and filled out individual difference measures (which included a self-efficacy scale). Only 86 participants successfully returned for the second session, during which they indicated how much success they had had at keeping their resolutions.

What does this mean for your resolutions?

The resolutions made by participants across all conditions were qualitatively similar (take a look at any list of popular New Year’s resolutions, and you’ll see the majority of the goals). As shown in the first two studies, more goals were set by people who believe self-control is unlimited and malleable than by any other people–that is, if you expect more success, you may increase the difficulty and number of tasks that you set for yourself. Self-efficacy did not have a significant effect on goal-setting.

As far as success goes, only the interaction between lay theory and self-efficacy was significant. If participants believed in limited self-control and were low in self-efficacy, they tended to give up more often, failing to achieve their goals. But if participants believed in unlimited self-control, self-efficacy had no effect; participants achieved just as many goals regardless, and people who set more resolutions were marginally more likely to succeed.

Mukhopadhyay & Venkatarmani realize that their research does not directly look at the relationship between lay theories of self-control and beliefs about one’s own amount of self-control and self-efficacy, and propose this as an area for future study. But in general, lay theories about self-control can determine how much success you’ll expect (and thus, how many goals you’ll set), and self-efficacy beliefs can determine how much success you’ll actually have.

References
Mukhopadhyay, A. & Johar, G.V. (2005). Where There Is a Will, Is There a Way? Effects of Lay Theories of Self-Control on Setting and Keeping Resolutions. Journal of Consumer Research, 31, 779-786 [PDF]

The longest Monday of my life

I recently returned to the US from Australia. The 14-hour flight took me from Monday morning in Sydney to Monday morning, again, in L.A. Crossing the date line messed up my sense of time enough without the added bonus of thinking I should be heading to bed just as the sun began to climb into the California sky.

You may be familiar with the concept: Jet lag. The catch-all name for circadian misalignment, the disruption of sleep cycles and circadian rhythms. If you’ve had the pleasure of crossing time zones in a jet plane, whether it was a mere three-hour hop from one coast of the US to the other or a trip to another continent, chances are, you’ve experienced some amount of jet lag.

The pathophysiology of jet lag

Normally, two systems–the homeostatic system and the circadian system–work together to produce a 24-hour sleep cycle. During the day, the homeostatic system slowly accumulates a ‘sleep drive,’ a desire to sleep that increases as a function of time spent awake. The circadian system generates an alerting signal in opposition to this sleep drive, which, during the day, keeps a person from feeling increasingly sleepy. An hour or two before bedtime, this signal subsides, and s/he realizes it’s time to hit the pillow. The sleep drive dissipates as a person sleeps and by morning (assuming a full night’s rest and possibly some coffee), s/he will be feeling alert and ready to go again.

Robert Sack wrote a delightful paper [PDF] on jet lag, by the way, which is where I’m getting much of my information.

So we’ve got a nice cycle of sleep. Jet lag is what happens when the homeostatic and circadian processes are misaligned. For example, the circadian system may signal a person to be alert when it’s not actually morning, or may be reduced during daytime hours, causing daytime sleepiness because the homeostatic sleep drive is no longer canceled out.

But I don’t want to be sleepy!

How do you beat jet lag? Robert Sack lists three primary approaches:

1. Reset the body clock
2. Prescribed sleep scheduling
3. Medication to counteract daytime sleepiness or insomnia

Let’s start with the first one, as it turns out to be the most complicated.

Resetting the body clock

The two most effective ways to reset the body clock are 1) through bright light exposure, and 2) timed melatonin administration. (But see below; fasting can also reset the body clock.)

Light is one of the most important cues about time of day and has the greatest effect on circadian timing (much smaller effects are seen from regular activities and meals, for example). Studies have shown that without light cues, totally blind people tend to have free-running circadian rhythms with an average period of 24.5 hours, instead of the usual 24. If a person is exposed to bright light early in the day, the person’s internal clock is reset to an earlier time; if exposure is instead in the evening, the internal clock is reset to a later time. Brighter light has more of an effect (such as the sun, at 3000 to 10,000 lux), though lower intensities (e.g., 100-550 lux) can produce changes.

Artificial light sources can be used to supplement daylight, to help reset a person’s internal clock to the correct new time zone when traveling. Alternatively, a person could wear very dark glasses, as light avoidance could help minimize the problems of light exposure at the wrong time of day or night.

Resetting the body clock, Part 2: Melatonin

Melatonin is a hormone that has been linked to the regulation of circadian rhythms and sleep cycles [PDF]. Melatonin is secreted by the pineal gland at night; secretion is suppressed by light exposure, and as such, the hormone can be thought of as a “darkness signal.” If doses of melatonin are administered in the morning, circadian rhythms will be shifted later; evening doses shift rhythms earlier. Timing of the doses is more important than amount per dose, though it remains to be seen what the optimal dose and optimal time of administration is–trials have been done with doses from 0.5 to 10mg, at times ranging from three days before departure to five days after arrival in the new time zone.

If doses of melatonin are combined with light exposure, the results are what you might expect: synergistic if both are administered to produce a time shift in the same direction (both earlier or both later); antagonistic otherwise.

Sleep, wake, sleep, wake

The second way to beat jet lag: Sleep at weird times. Slowly adjust your sleep schedule to match that of your destination, or keep your home sleep schedule for a while after you arrive. The problem with this is that your sleep-wake schedule won’t match up with that of the people around you, and if you need to be awake for breakfast at 7am or for a meeting in the afternoon, your sleep schedule may interfere. Use this method at your own risk.

Drugs for everything

Lastly, we have sleep medicines. As you might guess, hypnotic medications combat insomnia and stimulants fight off daytime sleepiness pretty well, because by definition, that’s what they do. Both benzodiazepine and non-benzodiazepine drugs have been shown to be effective in the first case; for the latter, the most common solution is to consume more coffee [PDF]. This works! In the study linked, subjects were treated with slow-release caffeine or with melatonin prior to a long eastward flight; the caffeine subjects were less sleepy than either melatonin or placebo. Granted, caffeine subjects also took longer to fall asleep later and awoke more frequently, but that may be a risk you have to take.

Lagging behind

Light, melatonin, drugs, strange sleep schedules. Of course, the only solution that will always work is time. The homeostatic and circadian processes need to realign, and while the aforementioned ways of beating jet lag can fast track the process, it still takes time.

UPDATE: I was alerted by a friend of the existence of further research of which I was unaware: Another way to reset your sleep-wake cycle is to stop eating. If you fast for about 12 to 16 hours, your body clock will reset, with whatever time you break your fast as morning. The Fuller, Lu, & Saper paper [PDF], published in Science, discusses the mechanism, though a more recent paper argues that the Fuller et al. results are inconclusive.

Billions and trillions

Step by slow, supercomputed step, we approach singularity.

This step: Two massively parallel cortical simulations, run at the Lawrence Livermore National Labs by Rajagopal Ananthanarayanan, Steven Esser, and Dharmendra Modha of the IBM Almaden Research Center, and Horst Simon of the aforementioned labs–these are the guys who previously simulated at the scale of mouse and rat cortices. They used a Blue Gene supercomputer (with a whopping 456 CPUs and 144 TB of main memory–just wait, ten years from now I’ll look back on this sentence and laugh at how little computing power and memory that is). The first, and larger, simulation included 1.6 billion neurons and 8.87 trillion synapses. Human brains still dwarf these numbers: roughly 20 billion neurons and 200 trillion synapses. But it’s a cat-sized step with the complexity and scale of a feline brain.

The first simulation used experimentally-measured gray matter thalamocortical connectivity from a cat’s visual cortex–the simulations neurons were connected in a biologically plausible fashion. Phenomenological spiking neurons, individual learning synapses, axonal delays, and dynamic synaptic channels were all included in the software. The second simulation, with 900 million neurons and 9 trillion synapses, had probabilistic connectivity.

Speed-wise, the researchers report that their simulation runs 2-3 orders of magnitude slower than real-time, when compared to a human cortex. With near perfect weak scaling (doubling the memory resource doubles the model size that can be simulated), human-scale models may be just around the corner… well, relatively speaking; the researchers predict it’ll happen in less than ten years. Just as soon as there’s a supercomputer super enough.

The research paper is also available at researcher Dharmendra Modha’s blog [PDF].

But bigger isn’t necessarily better

We may have to wait ten years for human-scale simulations, but we may not need a human-scale platform to be able to build intelligent AI. Researchers at Queen Mary, University of London suggest that bigger may not necessarily be better, when it comes to brains. A lot of complexity can be found even in tiny insect brains. Maybe it’ll be a swarm of honeybee robots that takes over the world!

The complexity of models

For a time, I was convinced that every model out there would not be an adequate model of what a human brain could do because every model out there had to simplify, and thus, that no model or computer software would ever be able truly intelligent until we had the computing power to make an electronic human. I knew there was value to models, but deep down, I retained the conviction that no model, no simulation, no AI would ever manage the same level of complexity or intelligence as a human without being, simply put, a human.

Fortunately, I was relieved of this notion around the same time I started taking Cognitive Science classes: Humans aren’t the only intelligent creatures, the point of a model is not to create the thing you are modeling, all models simplify some aspect (it’s just a matter of choosing which aspects are most important to get exactly right). The world may be its own best representation, as Rodney Brooks so aptly said, but that should not preclude us from simplifying the world to better understand how it works, nor should that, in return, prevent us from trying to simulate ourselves in software.

I, for one, am looking forward to watching the intelligent honeybee robots and the supercomputer human brains band together to overthrow the government.

We’re in the dark

Recent measurements of the cosmic microwave background (radiation leftover from the universe’s early hot and dense state) support the hypothesis that dark matter and dark energy make up 95% of everything in existence.

But what’s the matter?

Isn’t it fascinating and mind-boggling that we have almost no idea what the majority of the stuff in our universe is? There are dark matter and dark energy are not rather than explain what these mysterious stuffs are. E.g., dark matter is not just dark clouds of normal matter (called baryonic matter); it is not antimatter; it is not huge black holes. But it is 25% of the universe.

Current research on dark energy hasn’t faired better: Is it a property of space, as suggested by Einstein’s cosmological constant? Perhaps it’s a result of the quantum mechanics of space; maybe it’s a new kind of energy field. It’s also possible that Einstein was wrong. It wouldn’t be the first time a seemingly brilliant solution, explaining everything known at the time, was later replaced. Think “ether.” Think “animal spirits.” Think “caloric fluid.” That said, there’s nothing better to replace it yet. At least this time we’re acknowledging the fact that the names “dark energy” and “dark matter” refer to stuff we don’t yet understand.

The quest goes on

The Joint Dark Energy Mission, a space probe designed to study dark energy, has been in the works for a while now. The mission is currently in a tight spot as NASA, the Department of Energy, and the European Space Agency tussle over who’s in charge of which parts of the probe and who’s paying for what. Don’t you love international politics? A lot of people, such as the folks at the Cosmic Variance blog are up in arms about the disagreements–can’t we all just get along and do science?