Table of Contents
Christopher Symonds
Hello, I'm TV's Christopher Symonds. You might know me from such classics as “2 and a Half Threads”, “Special Victims Unit Testing”, and the mind-bending movie “Exception”.
News
05-Dec-2014 03:09:49PM-0700
Final Project Page has been posted.
15-Nov-2014 01:09:07PM-0700
Ok, so here's where I'm at:
After a conversation with Prof. Ackley, it was concluded that my model needed a lot of simplification. So back to the drawing board I went, and implemented the changes he suggested. That done, and several wasted simulation runs later during which I realized I had some implementation errors in my model, I've gone back to running simulations. Now, instead of varying the amount of resources on the board, I am varying the threshold by which the Sytizens will engage in their genetic behavior. Parochials now have a single behavior. Altruists have another. Thus, PAs will engage in both. PNAs and NPAs will engage in one or the other, and NPNAs will engage in neither. Both genetic behaviors are tied to an energy threshold, below which they will not fire. For example, if set to 20, no Sytizen with less than 20 energy will share with or attack another Sytizen. This threshold is now what I am adjusting over runs. And holy crap, I think I have a U-shaped curve.
The bad news is, this has placed me very much behind. Now, my model description must be redone. My figure 1 redone. And I have many more lengthy runs to do before I can produce graphs 1 and 2. The bright side is that I am pretty much working solely on this over the weekend, but I wonder if that will be enough time…
08-Nov-2014 10:05:54AM-0700
I completely forgot to make an update last week, so I guess I'll lump it in with this weeks, and attempt to keep it concise.
- I've completed 20 simulation runs of Paralta; 4 levels of increasing scarcity with 5 runs each. The results are not terribly exciting or interesting. I see PAs generally dominating across the board. What makes this somewhat dismaying is that the groups tend to have very little contact and interaction, particularly in the more scarce environments and the behavior and fitness of a PA is rooted in his interactions with outgroups. So I don't even know what this result means other than the likely root being an inherent flaw in my model.
- Regardless, I've done a write up of my model for presentation in next class. It's fairly bullet-happy, and I'm not sure that's an appropriate thing for a research paper, as I don't remember reading any with this many bullets. I guess the class will judge.
- I'm pretty sure I have the worst Figure 1 ever. Even having put my paper into IEEE format will not make this figure 1 look respectable. It's a train wreck.
All in all, the outlook is iffy. On the bright side, were I to do a project like this again, I would be much more comfortable in knowing the kinds of bumps to expect, and a better sense of where the pitfalls lie. That's a good thing.
26-Oct-2014 09:30:47PM-0600
I've been working sporadically over the week, so I'm just going to compile everything into one update for the week:
Graphing: I've installed gnuplot on my usb-untu and wrote a bash script that will convert my data files into nice graphs that do a great job of telling the tale of a simulation at a glance.
The bad news is, this has exposed all the horrible things wrong with my Element_Sytizen. After doing several runs of of a single team only and seeing a predominance of one kind of classification, I concluded something must be wrong in the implementation. After going through the code, there were not only issues with genetic behavior, but with breeding and movement as well. After some refactoring of the broken stuff, I tried to take Professor Ackley's advice and simplify the genetic behavior as much as possible. The following behavior algorithms are now in effect:
Parochial Altruists: Attack outgroup with 0.5 chance of success, no longer get energy for this, but opponent still dies. On failure, 0.5 chance of dying from the attempt.
Parochial Non-Altruists: 0.5 chance of stealing 1 RES worth of energy from outgroup. The PNA does not get to keep this energy if successful. On failure: 0.5 chance of losing 1 RES worth of energy.
NP-A: If NPA energy is over a threshold and a friendly has less energy than the energy surplus over that threshold, the NPA will give the friendly 1 RES worth of energy.
NPNA: Still just dancing.
This, along with some adjustments to global parameters (Increased breeding range to 4, RES pickup range to 2, Strike range to 2, Mutation odds to 1 in 250) the simulation runs now resemble something closer to sanity. Instead of looking like fish and sharks with swarms of colors chasing each other around the map, it now looks something more like Frobworld, with diffused dots chasing RES around the map and occassionally getting into scuffles with an outgroup. Runs with a single team now show more balance in categories (with the exception of NP-As which still tank fairly quickly, but at least appear on the board now.)
Here's an example run with 1 team only, RES produced at 1 in 200
And here's one with 2 teams, RES produced at 1 in 200.
I think I'm in good shape, and so am now cautiously transitioning to my science hat.
22-Oct-2014 08:54:16PM-0600
Finished reading Maley's paper in preparation for my defense next class. Having never defended a paper in this manner before, I'm not sure what to expect. My brother's recommendation is to put my back to the corner, drop the paper at my feet, and swing my arms around wildly, all while making extremely loud bird calls to confuse would-be attackers. So between that and carefully studying the paper, I should hopefully be able to put up a good defense.
Project
Profile on Dr. Thomas Ray
I've selected researcher Tom Ray as my subject for the researcher profile section of the course.
Project Idea(s)
Altruism | I am interested in studying the effects of altruism in the form of resource sharing between individuals in a population living in a given state of scarcity. Is there a 'sweet spot' of this kind of altruism that benefits the species as a whole that arises as a function of a given level of scarcity? How does one measure that kind of thing? Is it possible to model an environment of scarcity in a quantifiable way that is useful? Possible paper title might be “Optimal Altruism in Scarcity Systems' or 'Hey brother, can you spare an artificial dime?' |
---|---|
FrobWorld+ | Other possible topics include FrobWorld+, wherein we take peaceful frobs and put weapons in their hands, give them a sense of tribalism, maybe even allow them to specialize as gatherers, warriors, etc. Other wishlist capabilities include hoarding and resource management, communication, breeding and genetic crossover as opposed to spontaneous mitosis wherein the genetic propagation relies solely on mutation for evolution. Pack them with as much human-like capabilities we can give them within time constraints and see how their evolutionary paths unfold, and if we converge on any particular genetic pattern as dominantly successful. This is a bit weaker as I'm not sure what specific questions we might ask of this, rather it's a “This sounds like it would be fun, let's do it and see if something interesting falls out of it” kind of thing. |
Third Idea
The previous two ideas are, as you can see, both inside the box. This idea space is reserved for an idea that is outside the box. And when I've thought of one, I will put it here.
Comments
Feel free to leave a comment in this section. Don't forget your time stamp!