We had our first DenHUG meeting yesterday. It was just Ben Atkin and myself, but we had a good chat about Haskell and why we're interested in it. We're taking different approaches to learning Haskell, Ben is downloading and studying applications written in Haskell, while I'm reading Real World Haskell, and we're both experimenting as we explore the Haskell ecosystem.

Ben asked me what my expectations were for the DenHUG meetup group. I told him that it was an experiment to see if it would help me learn Haskell. This got me to thinking that I should probably have better defined goals for the group. Here's a rough cut:

• Learn Haskell and explore it's potential.
• Meet others interested in Haskell, and more generally, Functional Programming.
• Determine where Functional Programming works better then other programming paradigms and where it is a poor fit.
• Find out why one would choose Haskell over functional languages like Erlang, Ocaml, or Scheme.

Things are getting very busy at work, with travel that conflicts with PyCon 2010, and I've had to cancel my talk there. I was looking forward to it. Maybe next year.

I've been doing some thinking about Cyber Renaissance and the system management problems the company is trying to solve. It's still an early stage startup and we're exploring some ideas about using autonomic clusters of computers to do useful work. This is an interesting problem domain, and may prove to be profitable.

We're looking at using a functional programming language such as Erlang or Haskell to implement this since they promise improved reliability and effective use of the multi-core processors that are now mainstream. As we develop our ideas, we'll experiment with the functional programming paradigm to see how well it fits both the problem domain and our brains.

I recently downloaded the 2009-11-10 version of SLAPP (Swarm Like Agent Protocol in Python) and worked through the examples to see how it's coming along. It's still alpha quality and not organized as a package, but improving. Some file and directory names include spaces which is inconvenient for working on the command line. The code looks like Objective C written in Python. Tutorial 6 is under development but is functional. It converts a schedule.xls file to schedule.txt and fails if you don't have the xlrd module installed. Tutorials 7 and 8 are simply placeholders at this point. I also downloaded the Swarm documentation and Objective C source to help fill in the gaps.

I'm using Tutorial 6 as the starting point for a simple traffic simulation model. This consists of a four way stop intersection with the base case of drivers (agents) following the standard rule of proceeding through the intersection in the order they stop and yielding to the driver on the right when multiple drivers arrive at the intersection at the same time.

I'll massage the code from the tutorial to make it a little more Pythonic, package the core pieces to better support multiple models, and ensure compatibility with both Python 2.6 and 3.1. The tutorial has the beginning of a GUI interface using Tk which I may work on, though I'd like to see OpenGL and browser based interfaces as well.

I stumbled upon Mark's Daily Apple, the blog of "Primal Blueprint" author Mark Sisson. It presents his take on the paleolithic/evolutionary fitness and diet lifestyle. In a nutshell:

• Primal Blueprint Law #1: Eat Lots of Plants and Animals
• Primal Blueprint Law #2: Avoid Poisonous Things
• Primal Blueprint Law #3: Move Frequently at a Slow Pace
• Primal Blueprint Law #4: Lift Heavy Things
• Primal Blueprint Law #5: Sprint Once in a While
• Primal Blueprint Law #6: Get Adequate Sleep
• Primal Blueprint Law #7: Play
• Primal Blueprint Law #8: Get Adequate Sunlight
• Primal Blueprint Law #9: Avoid Stupid Mistakes
• Primal Blueprint Law #10: Use Your Brain

One could do worse.

The Libertarian party is 38 years old today. Happy Birthday!

In Small Worlds: The Dynamics of Networks between Order and Randomness Duncan Watts explores the effects of network connections on system behavior. Network effects are evident in the spread of epidemics, the function of the brain, the adoption of new technologies, and other disparate areas.

Small World networks are non-random and sparsely connected. They tend to contain clusters of closely connected notes with a few shortcuts to distant ones. The "six degrees of separation" from urban lore is an example of the small world phenomenon. Watts raises more questions than he answers concerning this emerging research topic.

Some thoughts from Armed Liberal on what it means to be a patriot. Patriots come in all shapes, sizes, and colors. Being human, they've made mistakes, but they've left us a legacy of peace, prosperity, and freedom. We should honor their memory today, forgive their mistakes, and do our best to enrich their legacy and pass it on to those who follow us.

I'm interested in Agent Based Simulation and have played with Swarm a bit. While Objective-C is OK, I prefer dynamic languages and have thought about building something in Python.

Pietro Terna has already done this as he describes in Agents in Simulation Models, using a Swarm-like Agent Protocol in Python. His SLAPP package is available here. SLAPP is still young, but can be used to build interesting models.

In Entering Space Robert Zubrin describes how humanity could graduate from being a planet bound species to an interplanetary, and eventually interstellar one. He categorizes civilizations by the extent of their mastery of local resources. Type I civilizations exploit the resources of their native planet. Type II civilizations achieve control of the resources of their home star system. Type III civilizations expand to multiple star systems.

As founder of the Mars Society, it's no surprise that Zubrin sees Martian colonization and development to be key, though he acknowledges the potential of Lunar and asteroidal resources. He believes that governments will lead the way to space with private enterprise following and providing support services. I'm more optimistic that private efforts will play a leading role.

Zubrin looks at potential technologies consistent with our current knowledge of physics that might enable humans to travel, live, and prosper in the inner solar system, the outer solar system, and interstellar space. The most striking point in his analysis is that relatively fast interstellar spacecraft that could carry humans would expend an enormous amount of energy. They could easily become weapons of mass destruction, a sobering thought.

Learning Probabilistic Relational Networks are a generalization of Bayesian Networks. They can take advantage of the large volume of data available in relational databases and it is claimed that they are more robust than Bayesian Networks.

Never Let Go is a collection of Dan John's writings on strength and conditioning training. Subtitled "A Philosophy of Lifting, Living, and Learning", it provides a pragmatic approach to navigating the tangled web of information about health, fitness, and athletic training. A certain amount of strength and conditioning is necessary for good health and is fundamental to fitness and athletic performance. How much and what kind depends on your goals, and Dan emphasizes that you need to need to stay focused on your goals.

The main points of Dan's strength and conditioning philosophy are:

1. The Body is One Piece.
2. There are three kinds of strength training:
   • Putting weight overhead
   • Picking it off the ground
   • Carrying it for time and distance
3. All training is complementary.

Each chapter is a lesson in the guise of an entertaining and enlightening story told by a master practitioner of the strength arts. Reading and rereading these stories will help you in your own strength practice, whether as a coach, athlete, or fitness enthusiast. As you read it you will sometimes think "I knew that", while realizing that you've just reached a better understanding. Dan teaches movements rather than muscles and you need to train the full spectrum of normal movement. However, if you try to emphasize everything, you end up emphasizing nothing, so he recommends a warm up that works a variety of movements which allows you to focus on specific goals in the main workout.

Since the body adapts to novel stresses, everything works but nothing works forever. Combined with everyone's unique genetics and history, this implies that you should try different things long enough to see how they work for you. If they don't work, move on to something else. If they do, continue with them until you stop progressing, then try something else. Keep a training log so you'll know what has worked in the past and can profitably be repeated.

"Never Let Go" is a worthwhile and enjoyable read for just about anyone. It's a great book on the pursuit of althleticism that should be read and re-read by anyone with more than a passing interest in health, fitness, and/or sports performance.

Duncan McGreggor has embarked on an interesting series of posts about cloud computing. Cloud computing is many things to many people, but Duncan's perspective is close to mine.

In The Wealth and Poverty of Nations, David Landes asks why some nations are very rich and others very poor. He examines the economic history of Earth in search of answers. He concludes that a combination of freedom, the rule of law, and competing interests have tended to generate the most wealth. Along the way he recounts many interesting historical episodes. Seems our government is heading the wrong way.

A friend recently founded ElderThink, a site devoted to Living longer, Living Well for elders and those who care for them. While I still have a hard time thinking of myself as an elder, my beard has become pretty gray. The site is a good source for information on dealing with aging on a day-to-day basis, unlike Fight Aging which focuses on cutting edge longevity research.

Stephen Kellert presents a philosophers view of chaos theory with his In the Wake of Chaos. He follows an introduction to chaos theory and its history with an exploration the philosophical implications. The sensitive dependence on initial conditions of chaotic systems combined with the limits to measure precision from quantum mechanics places limits on the predictability of many physical processes.

Kellert then poses the question: Why did it take so long for chaos theory to become a field of serious scientific inquiry? The commonly presented explanation is that lack of the necessary mathematical and computational tools delayed such explanation, but Kellert doesn't think this sufficient reason. Poincare laid the mathematical foundations in the late 19th century and digital computers were available in the mid-twentieth century, but the dynamic non-linear systems of chaos theory weren't investigated until decades later. Kellert finds this surprising and proposes social factors that kept chaotic phenomena from being considered interesting. I think he's right, though I don't find it surprising. Even pure research tends to be driven by the potential utility of the results.

Iron Mind: Stronger Minds, Stronger Bodies by Randall Strossen covers psychological aspects of weight training in considerable detail. While it contains some useful insights, many of the points are presented as stories which seemed contrived to me.

Volkswagen showed it's BlueSport concept roadster at Detroit. It looks like a great combination of fun and fuel economy.

Nassim Taleb has an essay exploring the limits of statistics over at Edge. It's about the contribution to the meltdown of the financial system by bankers and regulators putting too much faith in statistical models of risk. He emphasizes the importance of knowing what we don't know, and planning accordingly.

Taleb constructs a map which divides decision making into for quadrants in a two dimensional space. One axis divides randomness into two categories and the second divides outcomes into simple and complex.

He calls the first type of randomness Mediocristan and can be described by well defined mathematically with a strong tendency toward a particular value such as the Gaussian (or normal) distribution and exponential distribution. The second type of randomness, which he calls Extremistan, is less amenable to static analysis and may be described by such things as power law (or fractal) distributions and are likely to be sensitive to initial conditions and detailed history. The first type of randomness is dominated by typical values, while the second is dominated by extreme values.

The first quadrant describes games of chance and is a predictable type of randomness that provides the livelihood for casino operators. The third quadrant represents real world domains such as quality control where statistics is generally useful, though some inconvenient "outliers" may have to be ignored. The second quadrant doesn't seem to have much real applicability, though there may be some examples in decision theory literature. The forth quadrant is where statistics breaks down and we get into trouble when we rely upon it. Evolution, politics, economics, wars, etc. lie in the last quadrant.

The fourth quadrant is were we most want to assess risk, but are least able to predict it. As Will Rogers said: "It ain't what we don't know that gets us in trouble. It's what we know that ain't so."

In Search of the Warrior Spirit by Richard Strozzi Heckler documents a project to teach awareness training to a group of Green Berets. This training included meditation, bio-feedback, and Aikido. Strozzi Heckler seeks to separate the essence of being a warrior from the mass industrialization of modern warfare. While generally interesting, the book spent too much time on the author's angst about teaching professional warriors.