What does this have to do with entropy?
The insects that crashed, or contained logic errors, or that cornered themselves, had high entropy. The "dumb kid's" insect had low entropy.
Think about it.
Insects and Entropy
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Re: Insects and Entropy
#12The story is not that far fetched. Decades ago (I think) there was a computer simulated game designed to play out what is called the Prisoner's Dilemma hosted by professor Axelrod. And the winning program? It was the simplest one, which the author had named Tit-for-Tat.
Oh, but Tit-for-Tat didn't win because the other programs crashed.
Very true. It won because it tapped into a simple but persuasive idea about interpersonal dynamics -- only be benevolent if your opponent is benevolent. It succeeded with this simple strategy against much more complex schemes.
Re: Insects and Entropy
#13Re: Insects and Entropy
#14Occam's razor at work. The simpler the logic, the more likely it is that it does not contain unexpected faults than a system which has more complex logic.
The article claims that the kid's program contained lots of dead code.
Precisely, it could have been made simpler yet (trimming the fat) becoming a yet more perfect program.
Re: Insects and Entropy
#15So, the moral of the story is that your code should do one thing and do it well.
I read it as do as little as you need to
Re: Insects and Entropy
#16Same with website design. Sometimes plain old HTML beats the fancy CSS design with lots of moving parts.
Re: Insects and Entropy
#17I have a similar story to tell. As an undergrad in a course of robotics, we had to program a wheeled robot and all the robots would be place in an environment with obstacles. The robot should avoid crashing with the obstacles and the other robots. Extra points if the robots moved smoothly.
Me and my friend implemented a very simple algorithm. All the sensors measured distances to objects, and to every reading we would assign a vector whose direction oppose the one of the sensor and length, inversely "proportional" to the distance. Add all the vectors and move in this direction with a speed proportional to the length.
This turned out to work very well to avoid static obstacles and other robots. Most students implemented finite state machines. They crashed quite a lot and their movement was very clumsy, which I suppose was due to the fact that the transition of states was not very smooth.
To be fair, our success was a combination of luck and laziness too. If we had more time, we would have implemented a FSM too.
Re: Insects and Entropy
#18I have a similar story to tell. As an undergrad in a course of robotics, we had to program a wheeled robot and all the robots would be place in an environment with obstacles. The robot should avoid crashing with the obstacles and the other robots. Extra points if the robots moved smoothly. Me and my friend implemented a very simple algorithm. All the sensors measured distances to objects, and to every reading we woul…
Weird so many people went for FSMs. You would have thought that a simple literature search would have brought up all sorts useful nuggets. Given the scenario you describe - no goal other than avoid collisions, the scheme you implemented is basically a simplified potential field approach.
All that being said, I can appreciate the core of this story. I spent my final year implementing, testing, and optimizing D-Lite for a robot (basically a fancy incremental version of A), only to find out that in the end, given our sensor performance, the stock A* planner that came with it did almost nearly as well. Oops.
Re: Insects and Entropy
#19The story is not that far fetched. Decades ago (I think) there was a computer simulated game designed to play out what is called the Prisoner's Dilemma hosted by professor Axelrod. And the winning program? It was the simplest one, which the author had named Tit-for-Tat.
Oh, but Tit-for-Tat didn't win because the other programs crashed.
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Re: Insects and Entropy
#20I have a similar story to tell. As an undergrad in a course of robotics, we had to program a wheeled robot and all the robots would be place in an environment with obstacles. The robot should avoid crashing with the obstacles and the other robots. Extra points if the robots moved smoothly. Me and my friend implemented a very simple algorithm. All the sensors measured distances to objects, and to every reading we woul…
Weird so many people went for FSMs. You would have thought that a simple literature search would have brought up all sorts useful nuggets. Given the scenario you describe - no goal other than avoid collisions, the scheme you implemented is basically a simplified potential field approach. All that being said, I can appreciate the core of this story. I spent my final year implementing, testing, and optimizing D -Lite f…
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