A ‘Simple’ Neural-Network Model

My previous blog post summarized the main points of the Watts 2002 paper. At the very end of the post I mentioned ways we can extend the Watts model with neural-networks. Here I outline the steps of the neural-network simulation. Generally the model goes though an initiation step, a simulation step, and a cleanup step. In the initiation step, the agents are created and connected in a network. Then selected agents are seeded with a value before continuing onto the simulation step.

Expanding the Watts Model

I wrote a blog post and gave a seminar talk about the Watts 2002 paper. The next step is thinking about expanding the binary decisions with externalities model to a psychological plausible decisions with externalities model. This has been the goal of the multi-agent neural-network (MANN) project. Context from the Watts model From an information diffusion perspective, a cascade is the spread of information from an initial set (seed) of individuals (nodes).