Putting the magic in the machine since 1980.

## Tuesday, October 23, 2007

### Combinatorial Auction Model

One can visualize a combinatorial auction (with OR bids only) as a
graph with two types of nodes: bids and items. Each bid node is
labelled with the price of the bid and connected to all the items it
is over. This is the visualization I have implemented in my combinatorial
auction NetLogo model. It implements the branch-and-bounds
algorithm on the branch-on-bids tree as found in my textbook.

## Thursday, October 11, 2007

### Iterated Equiresistance Model

A couple of years ago I built this simple NetLogo model that
implements the iterated
equiresistance algorithm in randomly generated exchange networks,
as used by network exchange theory in Sociology. It now looks kinda
dated and needs to be cleaned up but I thought I'd post it
nonetheless. I'm using it in class as a demo.

## Wednesday, October 10, 2007

### Pareto Learning Model

I have posted a new netlogo model on pareto
learning which implements the algorithms from this
paper. This is a quick and dirty implementation for an in class
demo. As nearly always happens when I do these, I found a slight
problem in the paper. They specify two different ways in which the
agents choose an action. Namely, first they say that the agents choose
actions stochastically based on their expected utilities, then they
say that they choose their best action and with probability epsilon
choose a random action. After implementing both strategies it became
clear that the second one is the one they actually used. Clearly, this
was just a problem of the prose being a bit confusing (at least, for
me).

It is also interesting to note how such a small change in the
action choice method can have such large effects on the system's
behavior. Because of this I have to say that the results from this
model are not *stable*, thus they are not of deep significance.

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