Tag Archives: evolution

How to Survive on a Desert Island

Fish exhibiting swarming behavior. Or, what I imagine Bayes_Bots to look like.

For the last few months, a team and I have been aggressively competing* in the 2nd Social Learning Strategies Tournament. Here’s what it’s all about:

Suppose you find yourself in an unfamiliar environment where you don’t know how to get food, avoid predators, or travel from A to B. Would you invest time working out what to do on your own, or observe other individuals and copy them? If you copy, who would you copy? The first individual you see? The most succesful individual? The most common behaviour? Do you always copy, or do so selectively? If you could refine behaviours, would you invest time in that or let others do it for you? What if you then migrated – would you rely on your existing knowledge, or copy the locals?

The team consisted of a rocket scientist, a mathematician, a genetic engineer, and me.  Fortunately, the other three had enough brainpower to help us put together something interesting to submit.

The deadline for submission was Feb 28, 2012. Our team ended up using Baysian economics to put together a competitor.  If you’re interested, the abstract overview is below.

Bayes_Bots makes decisions based on the expected payoff of the moves in her arsenal: Observe, Innovate, Exploit, and, in the appropriate extension, Refine.  To decide which move to use, Bayes_Bots will look at the distribution of the learned payoffs from Innovate, and Observe.  Bayes_Bots uses Bayesian inference, to learn these distributions: she assumes that the values learned from Innovate and Observe can be modeled by an exponential distribution, and given a distribution on the payoffs associated with each arm, the means of the Observed distributions will follow a Beta distribution, while the payoffs from Observe follow an exponential distribution.  Bayes_Bots will discount older information as less reliable, using Pc as the probability that a given strategy’s payoff changes.

Bayes_Bots will Innovate rarely.  However, she will always Innovate on her first turn; this will help provide new raw information to the collective population of agents.

Observe_who. In the observe_who strategy, Bayes_Bots will not change her strategy.  The assumption is that information is equally valuable from all other agents in the field, regardless of their age, number of times they’ve been observed, etc.

Refine. Bayes_Bots will Refine one of her high-payoff moves at least once, in order to understand what benefit that might have to her overall expected payoffs.  Otherwise, Bayes_Bots will not change her strategy; if other agents refine their strategies, Bayes_Bots will learn the refined payoff.

Localization/Demes. When Bayes_Bots changes to a new deme, she will discard information about the distribution of payoffs from observed strategies.  She will retain information regarding the distribution of payoffs from innovated strategies, as well as the distribution of the means of the observed strategies, as these pieces of information are assumed to be useful across all demes.

If you want to read the full entry, let me know – I’m happy to share out the doc.  It also has our very complex math and equally complex Python code.

*by “aggressively competing” I mean “meet at a coffee shop once a week to pretend we know what we’re talking about and eat chocolate.”

Social Learning Strategies Tournament – Join the GTN Team

Game Theory Ninja is putting together a team to compete in the 2nd Social Learning Strategies Tournament.  From the website:

Suppose you find yourself in an unfamiliar environment where you don’t know how to get food, avoid predators, or travel from A to B. Would you invest time working out what to do on your own, or observe other individuals and copy them? If you copy, who would you copy? The first individual you see? The most succesful individual? The most common behaviour? Do you always copy, or do so selectively? If you could refine behaviours, would you invest time in that or let others do it for you? What if you then migrated – would you rely on your existing knowledge, or copy the locals?

Interested in joining the team? If you’re in the Bay Area and can commit to meeting up for at least an hour a week, send a quick email with a paragraph about yourself to lisa@gametheoryninja.com.  We move fast in Silicon Valley; submissions are due Wednesday, Sept 28 at 5pm PST.

Can’t join the team?  We’re still looking for a team name.  Leave suggestions in the comments.  The more ridiculous, the better.

Your “Choice Muscle” Needs Fuel, Too

The New York Times’s John Tierney just published an article about making decisions, called “Do you Suffer from Decision Fatigue?”  It’s one of the best, most in-depth articles I’ve read about the physiology of decision-making.  It’s long, but if you’re into this sort of thing, I really recommend reading it.

(The article is a good followup to my post from a few months ago, which discussed what economists Sheena Iyengar and Tim Harford think about this topic.)

High level summary

  • Making decisions is difficult work, so we get tired of doing it.  At the end of the day after we’ve made many decisions, we either make worse decisions or no decisions at all.
  • We make better decisions when our brains have access to glucose.  This is why we frequently crave sugary foods after a series of tough decisions.  However, having a constant supply of glucose from protein-rich foods ensures better overall decision-making throughout the day.

And who has the best self control?

People with the best self-control are the ones who structure their lives so as to conserve willpower. They don’t schedule endless back-to-back meetings. They avoid temptations like all-you-can-eat buffets, and they establish habits that eliminate the mental effort of making choices. Instead of deciding every morning whether or not to force themselves to exercise, they set up regular appointments to work out with a friend. Instead of counting on willpower to remain robust all day, they conserve it so that it’s available for emergencies and important decisions.

“Even the wisest people won’t make good choices when they’re not rested and their glucose is low,” Baumeister points out. That’s why the truly wise don’t restructure the company at 4 p.m. They don’t make major commitments during the cocktail hour. And if a decision must be made late in the day, they know not to do it on an empty stomach. “The best decision makers,” Baumeister says, “are the ones who know when not to trust themselves.”

The post is available here.

Robert Tercek – Information + Transformation

I promised not to post on every single speaker at Humanity + this time around, but Robert Tercek’s talk was just too thought-provoking and intriguing to skip over.

According to his bio, Tercek is “one of the world’s most prolific creators of interactive content.  He has created breakthrough entertainment experiences on every digital platform, including satellite television, game consoles, broadband Internet, interactive television and mobile networks.   His expertise spans television, telecommunications and software.”

His premise was that the intersection of information technology and human biology is going to herald a new era of human development.  Tercek noted that we’re currently in the “Era of B.S.” – where B.S., he said, stands for Before Singularity.

However, Tercek noted, perhaps we’re looking at the development of humanity through the wrong lens.  The media tends to portray the future in terms of “before” and “after.”  That is to say, right now, we’re “before” some mysterious, magical, transforming event, and after this event, humanity will enter an era that is unrecognizable and will have virtually nothing in common with humanity as we know it today.

Instead, Tercek suggested, we should look at societal development on more of a continuous scale; humanity is evolving constantly.  While there are a few technological developments that have profoundly impacted this developmental process, such as speech, writing, and print, it isn’t necessarily reasonable to suggest that there will be one single moment that will completely transform humanity.

From my perspective, Tercek’s main takeaway message was that value is shifting away from products – physical objects – to data, or virtual objects.  According to Tercek, the U.S. sales of virtual goods will exceed $2 billion in 2011.

As a quick aside, this relates directly to the idea of value shifting away from products towards anything else less tangible: intellectual capacity, creativity, time, services, etc.

Tercek’s talk included a lot of great statistics and specific examples, as well as a dearth of historical information.  He referenced the impending internet of things multiple times.  Not only that, but he was an excellent presenter – enthusiastic and compelling.

Some attendees mentioned that Tercek’s talk didn’t have a lot of new information.  However, Tercek’s talk did exactly what it was supposed to do – get the audience excited about the future, and especially the future that includes the next two days of discussion about transhumanism, futurism, artificial intelligence, technology, and more.

The GPS of your Mind

Alex Terrazas is the President and Chief Scientist at MediaBalance, Inc.  The company’s mission is to bring high technology and behavioral psychology to bear on the nation’s most critical health problems.

In his talk, titled “What Train-Driving Rats Can Tell Us about Memory in Virtual Environments,” Terrazas talked about cognitive mapping, which is, basically, how your mind creates geographic maps.  Terrazas equated it to the GPS of your mind.  What are we doing to our brains, he wonders, by using all of this mapping technology, like Google Maps, GPS, and Mapquest?  Do these technologies change the way we synthesize and store locational information?

Terrazas focused on the hippocampus, where spacial location information and memory is stored.  His conclusion is that, in order to understand our physical surroundings, or the layout of a city, we may need to physically walk around in order to map it to our brains.  That is to say, we need to walk around – not use GPS devices or Google Maps – to understand where things lie relative to each other.

This has profound implications for the future of virtual reality and virtual learning.  It could be that there are some things that we do need to learn the traditional way – i.e., physically, or in person, and not virtually.

Terrazas concluded: “We either need to throw away our GPS devices or find another use for our hippocampus.”

I followed up with Terrazas via Twitter after the event – I’m interested in learning more.  I’ll post on whatever I find out.

Thinking about Thinking Recap

In the Information Overload series, we discussed the concept of distilling information down to manageable, bite-sized summaries.  In the Thinking about Thinking series, we talked about the need for deep thought and fleshed-out ideas.

For those of you in the Information Overload camp, here’s a summary of everything we talked about in the Thinking about Thinking series.  For those if you who want to read more, click through to read the entire series, in all of its glory.

  1. Thinking About Thinking. In this introductory post on how technology is rewiring our brains, we looked at some of the reasons this series is worth your time to read.  These included our increased penchant for multitasking, the ability of internet use to change our mental processes, and our affinity for each new electronic notification text message.
  2. Do We Really Need Deep Thought? The media we consume is decreasing in size, and, thus, depth of information.  Does that mean our thoughts are adjusting accordingly?  Most scientific breakthroughs actually do require deep thought – the “Ah-ha” moment is a myth.
  3. Are We Addicted? Our Brains On Technology. This post looks at the science behind addiction, and how some of that science shows our brains react to technology in the same way they react to other addictions.
  4. The Opposite of Technology. Studies show that being in – or thinking about – nature causes our brains to make connections.  Conversely, being in or thinking about man-made environments, like cities and highways causes our thoughts to become scattered and jumbled.
  5. Getting off of Social Media. This post took it one step further, and  looked at organizations and people who are turning off their technology and social media connections.  We borrowed the term Countertrend – a social backlash to a trend – to describe the phenomenon.
  6. Conclusion: Circuits and Cerebellums. In this final post, we talked about some suggestions for dealing with all of this technology.

On Monday, I’ll be attending FailCon 2010. According to the website, “FailCon is the premier conference on start-up failures and how to prepare and recover from them.” Panelists include representatives from Etsy, the New York Times, Formspring, Twitter, Zappos, and more.  Look forward to posts about failure – then subsequent success.

Do We Really Need Deep Thought?

 

The Notorious Newton

 

This is the second part of “Thinking about Thinking:” a  series of posts about how our brains react to technology.

A few weeks ago, I was having a discussion with a friend who works in the publishing industry.  We were discussing the future of the long-form novel.  On Twitter, for example, an entire thought – and sometimes more than one thought – is contained in a mere 140 characters.  What does this mean for the future of novels that are 140 pages, or longer?  Will we be able to pay attention to anything as monstrously long as a novel?

While thinking about thinking, one theme has repeatedly surfaced: the media we consume is rapidly decreasing in size.   Status updates, e-mails, and Tweets are often less than a sentence in length.  There’s a worry that our attention spans are appropriately adjusting.  Our thoughts are more scattered, haphazard, and disconnected.  Are we skimming the surface of important concepts and ideas?  Is Socrates-style deep thought disappearing?

To answer this, I want to address the idea of the “Eureka!” or “A-ha!” moment. Continue reading