thoughts

Multi-team Systems

A multi team system consists of multiple teams where each team may have their own goals, but system in general has a common ultimate goal http://en.wikipedia.org/wiki/Multiteam_system.  This is really interesting.  I think that this would be an interesting direction to move bounties.

Also, on a different note, I think that a survey of this field would be useful.  Especially since I think those in the multiagent community should start to think in this manner.  I did some googling and I thought for sure that the robocup rescue simulation league would have some research on this topic.

As always I have to go back over my posts and it seems like I had an idea for multi-teams but in terms of fuzzy sets.  https://drewsblog.herokuapp.com/?p=1621.

Car insurance data

Did you know that auto insurance companies allow you to look up a quote online.  All you need is your name, address and date of birth and they will show you your cars!  That means you can with a little effort find out what cars people have!  Year and Model at least.  That could be valuable info for sales or targeted advertisements.  The crazy thing is that the website does not require you to agree that you are who you filled in the box says you are!  So, technically I don’t think you would be doing anything illegal.  Crazy.

fun autonomous vehicle ideas

Would be cool in the future with autonomous cars we will be able to have events where instead of having stations in a building that you walk to you would be in cars.  And whenever you switched you would change cars.

 

Bathroom car!  Would be too cool to have an autonomous bus/car that just drove around the city and people could request it and you would be able to go to the bathroom in it.  It could connect to the back of your car and you could walk into it.  Sensors would be able to monitor when you needed to go to the bathroom so that those vehicles could be positioned appropriately.

 

Entangled FindSet

Would be cool to use quantum entanglement to do instant FindSets (seeing if two elements are contained in the same set) for Kruskal MST algorithm.

Say each vertex is a photon.  Whenever you do a union you entangle the photons.  Then all you have to do to compare if the photons belong to the same set is to see if they are entangled.

This FindSet operation is already really fast O(lg*n).  However, this would be a constant time lookup.

What would the rest of the quantum MST algorithm be?

 

 

 

tv channel

The animation for the channel number on our tv (you know how when you change the channel it tells you what channel you are now on) changed today.  Made me wonder how that happens.  I thought that was defined by the tv… Strange.

Spacial-temporal clustering

I think that idea is actually a field.  Specifically spacial-temporal clustering.  There are a lot of highly cited papers in this field.  Also, it seems like it sort of tapered off in the mid-2000s.  I don’t see any mention of it being applied to a multiagent system other than for cars.

Ponderings on an old topic

See people in general are getting in each others way when in a crowded environment.  When there is a group of people that are working together in this crowd, their removal would cause the system to

The idea is to try and find the least noisy, as the less noisy the

I’m back to wanting to be an agent in a system of unknown but observable agents.  I want to learn what the alliances and correlation are between people and agents in the system.  I want to be able to take a birds eye view and be able to identify outliers, who is working together or how as an agent could you disguise yourself better so you aren’t detected.

We as humans are able to look at a crowd and we can observe patterns and group dynamics and interesting things, the outliers.  We do this very well.  A computer on the other hand even when looking at a simulated environment probably wouldn’t do as well as a human in grouping a crowd given a birds eye view.  As a human we are able to not only take into account the directional movement, but also profiling and predict then where you expect them to travel.  We know what normal looks like, we are aware of it what it looks like in most scenarios.

How can you define that mathematically.  What makes observing this mass of agents moving about different from a bunch of particles randomly moving about in the eyes of the observer.

Fun problem

David had an idea for a problem:

Given N individuals, each individual must, say, play a game with M other individuals.  The length of the game is stochastic and dependent on who is playing the game.  Describe an algorithm that will optimally group the individuals such that each individual has to wait the minimum amount of time to play with all of the other combinations of individuals.

Originally the problem was stated with M=2.

An extension would be what if N is changing with time.  Meaning new people come and go.  Can the algorithm be robust to this?

So, this seems like it could be approached through a combination of methods:

Stochastic processes (for the arrival and finish times)

Graph Theory / Combinatorics (for the pairing)

Optimization (for the scheduling)

I’m sure that there are other ways, but I think that this problem needs to be solvable pretty quickly in order to be useful…

HyperNEAT and facial recognition

So, I know that facial recognition is pretty decent, but I think that HyperNEAT would be pretty good at doing this.  I think that it would be able to take advantage of the geometry of the face in order to better characterize the face.  I have found a paper that used HyperNEAT on digits, and it did not do extremely well.  They found that HyperNEAT is good at extracting useful features that could then be used to classify.  So, maybe that would be something else to look at.