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AB-CE/abce: ABCE the Python Agent-Based Computational Economy Platform

Authors: Davoud Taghawi-Nejad; rht; a4d442663580;

AB-CE/abce: ABCE the Python Agent-Based Computational Economy Platform

Abstract

ABCE is a Python based modeling platform for economic simulations. For simulations of trade, production, and consumption, ABCE comes with standard functions that implement these kinds of interactions and actions. The modeler only implements the logic and decisions of the agents; ABCE takes care of all exchange of goods and production and consumption. One special feature of ABCE is that goods have the physical properties of goods in reality. In other words, if agent A gives a good to agent B, then - unlike information - agent B receives the good and agent B does not have the good anymore. That means that agents can trade, produce or consume a good. The ownership and transformations (production or consumption) of goods are automatically handled by the platform. ABCE models are programmed in standard Python, stock functions of agents are inherited from archetype classes (Agent, Firm or Household). The only not-so-standard Python is that agents are executed in parallel by the Simulation class (in start.py). ABCE does support an accounting framwork for financial simulations: ABCESL can be downloaded here. Install with: python3 -m pip install abce The documentation is here: http://abce.readthedocs.io/ An example is here: Insurance Market A code example is here: Jupytor Tutorial More code examples are here: (https://github.com/AB-CE/examples

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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