Block Matrix Formulations for Evolving Networks

Block Matrix Formulations for Evolving Networks

Many types of pairwise interaction take the form of a fixed set of nodes with edges that appear and disappear over time. In the case of discrete-time evolution, the resulting evolving network may be represented by a time-ordered sequence of adjacency matrices. We consider here the issue of representing the system as a single, higher dimensional block matrix, built from the individual time-slice...

Cooperative Co-Evolving Neural Networks for Robosoccer Simulation

Evolving Formulations: Sharing Complex Information with Clients

Psychological formulations are central to cognitive behavioural approaches. The use of such formulations presents a number of difficulties when working with clients with psychotic problems. Despite this, sophisticated psychological formulations can be collaboratively developed with psychotic clients. This paper presents one method of developing such formulations through an evolutionary process....

Open-Pit Block-Sequencing Formulations: A Tutorial

A classical problem in the mining industry for open-pit mines involves scheduling the production of notional three-dimensional production blocks, each containing a predetermined amount of ore and waste. That is, given operational resource constraints on extraction and processing, we seek a net present value-maximizing schedule of when, if ever, to extract each block in a deposit. We present a v...

Renormalization group for evolving networks.

We propose a renormalization group treatment of stochastically growing networks. As an example, we study percolation on growing scale-free networks in the framework of a real-space renormalization group approach. As a result, we find that the critical behavior of percolation on the growing networks differs from that in uncorrelated networks.