We introduce a simple agent-based model which allows us to analyze three stylized facts: a fat-tailed size distribution of companies, a `tent-shaped' growth rate distribution, the scaling relation of the growth rate variance with firm size, and the causality between them. This is achieved under...

We introduce a simple agent-based model which allows us to analyze three stylized facts: a fat-tailed size distribution of companies, a ‘tent-shaped’ growth rate distribution, the scaling relation of the growth rate variance with firm size, and the causality between them. This is achieved...

Statistical mechanics is used to derive a new learning rule for a feed-forward neural network with one hidden layer. Generalization to multilayer neural networks is straightforward, and proceeds in the same way as backpropagation.

Addressing issues of social diversity, we introduce a model of housing transactions between agents who are heterogeneous in their willingness to pay. A key assumption is that agents' preferences for a location depend on both an intrinsic attractiveness and on the social characteristics of the...

We consider the properties of multi-class neural networks, where each neuron can be in several different states. The motivations for considering such systems are manifold. In image processing for example, the different states correspond to the different grey tone levels. Another multi-class...