I would like to see if game theory and measure theory (in terms of swarms) can be merged to gain a better theoretical understanding of large complex systems of learning agents.  I have been reading http://tinyurl.com/mathswarm which describes some of the mathematics behind swarms.  Based on this article they use measure theory to model swarm so I have been learning about measure theory.

Innovation and learning seemed to develop more quickly with a larger population. Like comparing europe to the native americans. So I think that it would be wise to try to see how large groups of agents who were grouped doing different tasks whether innovation would emerge.

Like have a huge “soup” of agents and have different goals for different populations of agents. Will those with similar goals learn to cooperate.

If we limit resources will innovation emerge by having different populations cooperating to create a hirarchy to accomplish their respective goals?

Essentially, when a large population with differing goals but limited by the same resources will they learn to innovate in order to accomplish their goal or will they fail.

In the macro the micro complex actions apear to be simple effects. So, in essence we have a swarm.
Start listing of large multi agent systems that might also be swarms:

traffic networks including internet, cars, planes, and any other type of transportation routing.

learning in multi agent systems when others don’t learn?

At what point does the macrophenoma of a MAS appear as a swarm like behavior?  Then in a large multiagent learning problem could the agents be viewed as swarms instead of agents?  Can an algorithm be created to discover the swarm behavior of a large system composed of MARL agents?

Well I was able to export the wp_posts table from phpMyAdmin at freehostingcloud.  Then I had to change some of the id’s in the exported sql so that they didn’t conflict with those that were already used.  I imported the data into wp_posts.  Then I ran this sql

UPDATE wp_posts SET guid = replace(guid, ‘http://drew.freehostingcloud.com’,’http://drew.heliohost.org’);

so that the posts would actually work!

Hi,

I used to be at drew.freehostingcloud.com and I had to switch because for some reason freehostingcloud took my website and a bunch of other people’s sites on Sunday.  I even got on the forum to see what was up (http://www.freehostingcloud.com/forum/thread-can-t-access-website).  Thankfully I was able to still access the backend and get all of the data.  So, I switched to heliohost.  They are much faster, but occasionally I get a 500 error and I just have to refresh the page.

 

 

“Less work has been done on formal methods of decomposing tasks (and behaviors) into subtasks (sub-behaviors) appropriate for multi-agent solutions, how agents’ sub-behaviors interact, and how and when learning of these sub-behaviors may be parallelized.” (An Overview of Cooperative and Competitive Multiagent Learning)

I think that this would be an interesting problem to explore. I found that the problem of decomposition is also a major problem in engineering. They have come to the point were the number of variables in a problem are in the 1000s and an expert is not always available. Based on the paper, The State of Problem Decomposition in Engineering Design, solving this problem is useful. So, I am going to research how others are solving the decomposition problem and combine that with multiagent learning to try to solve real life engineering problems.

Well now I am at GMU and I am working on adding NEAT to ECJ! Back when I was learning about HyperNEAT I neglected to read about NEAT. Which now that I have been reading about it I wish I had taken the time. Then I would have known that what I called fault tolerance is called ablation testing and this testing was performed on NEAT!

I was accepted to present a poster about my research into the fault tolerance of HyperNEAT at the CCSC 2010 Conference at Juniata College. I put my research paper on my website at http://drew.freehostingcloud.com/research/hyperneat/fault-tolerance-of-hyperneat.html.

I created a capture the flag game to explore the capability of cooperative teams in a competitive environments using hyperNEAT.  I want to know if competing teams can learn when it is in their best interest to cooperate with a competing team.  I made a short video of my progress seen below:

Can an evolved hidden layer in the substrate handle faults not only in the output layer but also in the hidden layer without being trained with example faults?  I must first train it to get to the goal.  Then I should set one of the nodes in the hidden or output layers to be zero to test for fault tolerance.

If this doesn’t work I think that I need to move the output layer nodes to compensate since it is based on geometry.