On the ground at CppCon 2014

I’ve just returned from the week-long CppCon 2014 in Bellevue, Washington. Here’s what I experienced.

I’ve absorbed a great deal from a variety of C++ developer conferences – CppNow, Going Native, C++ And Beyond – but always virtually, via video and webcast. This was an opportunity to jump into the thick of things and participate in person. With community heavyweights like Herb Sutter and Scott Meyers in attendance I knew the content would be stimulating and informative. (Honestly, the speaker list featured nearly every name in the “C++ royalty” that you could imagine. I smiled to myself seeing Bjarne Stroustrup standing in the registration line like he was just another attendee.) So when the conference’s early-bird admission opened in March, I eagerly sent in my hard-earned dollars and blocked off the week of September eighth on my calendar.

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Steering Behaviors for Ruby game dev now on Github, Rubygems

I just released my Steering Behaviors package to Github, and an accompanying Gem to Rubygems.

If you’re building a game, you’ll want your game agents and characters to exhibit realistic motion. A standard way of doing this is with ‘steering behaviors’.

The seminal paper by Craig Reynolds established a core set of steering behaviors that could be utilized for a variety of common movement tasks. These include such behaviors as predictive pursuit, fleeing, arrival, and wandering. This Ruby library can accomplish many/most of those tasks for your Ruby / JRuby game.

The basic behaviors can be layered for more complicated and advanced behaviors, such as flocking and crowd movement.

Embellishments and expansions are planned, but this is working software you can use to drive your own game’s characters. (I’m using it in my own game programming.) The Github repo includes working graphical examples, and you can install the Gem for easier and more direct use in your own game.

Pull requests are enthusiastically encouraged.


On Github: my Fuzzy Associative Memory (FAM) package

I’ve just released to Github my working fuzzy logic module, Fuzzy Associative Memory.

A Fuzzy Associative Memory (FAM for short) is a Fuzzy Logic tool for decision making. It uses Fuzzy Sets to establish a set of rules that are linguistic in nature; examples might include:

  • “If the room is a bit warm, turn the fan up a little bit”
  • “If the orc’s hit points are a little low, retreat from the enemy”
  • “If the ship is off course by a little bit, correct just a little to the right”
  • “If the bird is much slower than the flock, speed it up a lot”

As you can see, the rules are deliberately vague and use qualifiers like “a little” and “a lot”. This is the nature of fuzzy sets; they capture such human fuzziness in a way that extracts highly natural behavior from the fuzzy rules.

It has a wide range of applications:

  • Industrial control, such as governing a fan to keep a room at the “just right” temperature
  • Game AI, such as giving human-like behavior capabilities to NPCs
  • Prediction systems


This is working, functional software. It currently supports:

  • Triangular fuzzy sets for input/output
  • Larsen Implication (scaling)
  • Atomic antecedent propositions (if A then Z)

To do:

  • Trapezoidal (and other shapes) for fuzzy sets
  • Hedges (‘very’ and ‘fairly’)
  • Mamdani Implication (clipping)
  • Composite antecedent propositions (if A or B, then Z)
  • Additional examples


The bin directory contains the following examples:

  • hvac_system_example illustrates how a FAM could govern an HVAC fan unit to maintain a constant, comfortable temperature

Get it here!

Force maximum performance for the NVIDIA driver in Ubuntu Oneiric

The NVIDIA X Server Settings app for Linux lets us tune the performance of our NVIDIA display adapter. On a laptop this is especially important as it lets you enable the power-saving features of the adapter to extend battery life. The adapter (and the settings app) default to “Adaptive” mode, which is a balanced mode that can scale up for performance but scale down for battery-savings.

The problem with Adaptive mode is that it doesn’t kick in as quickly as you might like. You’ll notice choppy behavior when scaling windows in Unity, etc. So if you customarily employ your laptop “like a desktop” or just want to force full-time maximum performance mode, the settings app will let you do so.

But wait, there’s a catch: the performance settings don’t seem to persist across reboots or even across logout/logins. The adapter will revert to Adaptive mode every time. This necessitates the annoyance of remembering to run the X Server Settings app each time you log in in order to re-set the power mode.

I have good news. There’s a straightforward hack to force maximum performance while on A/C power and fall back to the adaptive strategy while on battery. And the beauty of the hack is, you don’t need to touch the NVIDIA X Server Settings app at all for this. All you have to do is add a few configuration items to your Xorg configuration.

In Ubuntu Oneiric 11.10, you no longer edit the xorg.conf file like you did in previous distributions. You simply place configuration files in /usr/share/X11/xorg.conf.d/ and they will be loaded at X startup. For this hack, make a file /usr/share/X11/xorg.conf.d/05-nvidia.conf and put in it:

Section "Device"
Identifier "MyNvidiaDevice"
Driver "nvidia"
VendorName "NVIDIA Corporation"
BoardName "NVS 140M"
Option "RegistryDwords" "PowerMizerEnable=0x1; PerfLevelSrc=0x3322; PowerMizerDefaultAC=0x1"

Note that Identifier, BoardName etc. are indicative of my Lenovo Thinkpad T61 and may not match your own hardware. However, these lines are largely irrelevant to the way X runs. The key is the Option line. These configuration items direct the NVIDIA adapter how to handle performance scaling.

You can see exactly what these hex values mean and learn some other possibilities for the values by consulting this reference.

Hey, is that kitchen timer TSO’d?

I saw this picture of the space shuttle Atlantis this morning, and it made me smile.

Chris Ferguson, STS-135 commander, is pictured on the flight deck, surrounded by sophisticated, highly techn… hey wait! That’s a kitchen timer!  Not just any kitchen timer, but the very one that we have in our own kitchen:

My personal jury’s still out on whether this is one small step for Atlantis, or one giant leap for CDN Kitchen Timer.

Easy Doxygen code snippets for Xcode 4

Fred McCann has two great blog posts describing how to document  your Objective-C code with Doxygen, a popular and standardized documentation system for C, Java and other languages. His posts are extremely well-written and definitely worth a read; he takes you all the way from a basic introduction to Doxygen to generating the Doxyfile output.

But in Xcode 4 you don’t need to use a complicated scripting system to produce commonly-used Doxygen-compatible documentation. Xcode has a “snippets” facility that comes pre-populated with a variety of Objective-C snippets; let me show you how to leverage them.

Simple Doxygen documentation for a method might look something like this:

Compute the distance to another waypoint in nm.
@param other the other Waypoint
@returns the distance in nm

Why type all that over and over again? (And this is only a small subset of what Doxygen can do. In truth, the Doxygen system is very rich and, frankly, as complicated as you want to make it. Note that in this post I’m not covering Doxygen itself, just creating the code snippets.)

In Xcode 4 I use “dox <TAB>” to insert my custom method-documentation snippet. Here’s how you can do the same:

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  1. Activate the right-hand Utilities drawer and in the bottom of it, click on the curly braces {} to activate the Code Snippet Library.
  2. In the code editor, type or paste the code that you want to turn into a snippet; highlight it all.
  3. Drag the highlighted code to the Snippet library. (It can be stubborn and not want to drag. Holding the mouse button down for a moment before dragging seems to help.)
  4. Your snippet has been added to the Library; click once on the snippet and a callout window will show you the snippet and permit you to edit it.
  5. Add your own descripton, completion shortcut, etc. Any text you surround with <# #> marks will be highlighted with a blue bubble for quick tabbing and substitution.

Here’s the full snippet that I employ. It’s fast and it encourages proper code documentation.

 @param <#parameter#>
 @returns <#retval#>
 @exception <#throws#>

CNN covers HealthWeaver, my team’s software for cancer patients

At the University of Washington I am a Software Architect in the Department of Medical Education and Biomedical Informatics (say that three times fast!) where I am embedded with a cancer research team.  We are working on ways to use software and the Internet to improve the lives and well-being of breast cancer patients.

On April 16 CNN profiled our HealthWeaver software and interviewed my professor and team leader, Dr. Wanda Pratt.  From the UW Information School News:

Dr. Pratt’s work with cancer patients profiled by CNN

CNN.com features a story about the work of UW iSchool Associate Professor Wanda Pratt and her team. The team has developed an online system called HealthWeaver. HealthWeaver includes a social networking tool, and aims to help cancer patients manage information about their care, get their questions answered and interact with others who can aid them in their treatment.

CNN reporter Elizabeth Landau interviewed Dr. Pratt and Biomedical and Health Informatics Ph. D. student Meredith Skeels after their research presentations at the ACM Conference on Human Factors in Computing Systems in Atlanta this week. Other members of Pratt’s team include Kent Unruh, who was instrumental in formulating the idea; Chris Powell, who programmed the system; and many breast cancer patients and survivors who contributed to the design. The HealthWeaver core research team includes Andrea Civan Hartzler, Pedja Klasnja, and Marlee Mukai.

The full CNN article: Social networking makes it easier for patients to ask for help