Thanks! We have some network features in the pipeline (including better viz) and will be introducing some stdlib functions to help in the coming days. :)
We have some users representing networks in the 3D viewer at present, and have seen three ways implementing networks to date:
1. Edges are represented as agents. They are used to store properties such as edge length, and to provide nodes with a way of accessing other nodes.
2. Edges are represented AND USED as agents. Edges not only store properties but themselves exhibit behaviors.
3. Nodes are given a network object which contains information about their network neighbors and all relevant properties (such as directed/undirected edge, edge length, etc...)
Re: your question around experiments... yes to all three (parameter sweeping, Monte Carlo, and sensitivity analysis), and a bunch more. We'll be shipping this alongside H-Cloud. More on that in the full explainer at https://hash.ai/about/mission
Thanks for giving the beta a spin! Happy to chat in more depth over on our public Slack.
We have some users representing networks in the 3D viewer at present, and have seen three ways implementing networks to date:
1. Edges are represented as agents. They are used to store properties such as edge length, and to provide nodes with a way of accessing other nodes.
2. Edges are represented AND USED as agents. Edges not only store properties but themselves exhibit behaviors.
3. Nodes are given a network object which contains information about their network neighbors and all relevant properties (such as directed/undirected edge, edge length, etc...)
Re: your question around experiments... yes to all three (parameter sweeping, Monte Carlo, and sensitivity analysis), and a bunch more. We'll be shipping this alongside H-Cloud. More on that in the full explainer at https://hash.ai/about/mission
Thanks for giving the beta a spin! Happy to chat in more depth over on our public Slack.