We wanted flying cars, instead we got 140 characters

One of the immediate goals of the Yupana project is to go beyond an academic exercise and prove the conceptual viability of Agent Based Modeling approach in a real-world market simulation and predictions application. The crypto-asset ecosystem, and Nakamoto Terminal platform, specifically, provide a perfect testbed thanks to a vast amount of time-stamped data, an active developer community, and a scalable infrastructure with access to multiple 3rd party services.

As stated in the previous post, Yupana - Global Vision, conventional modeling techniques for simulating complex environments have relied on a set of fixed rules to govern how the model is to function. Agent based models (ABM) have been used for this purpose, to represent complex systems such as those in evolutionary biology or economics. While methods of ABM have been effective for specific use-cases, they fail to be generalizable and scalable over multiple systems. Popular heuristics such as…

Complex systems like those in biology, economics, or ecology are difficult to represent and properly understand. Complex interactions, emergent properties, and high dimensionality make it difficult to disentangle the governing rules and systemic properties when trying to model a given environment. We often depend on external tools to help us see particular patterns that are otherwise non-salient. These tools help us to better understand narrow relationships, aggregate and filter large sets of…