.. Agent-Based Computational Economics documentation master file, created by sphinx-quickstart on Mon Sep 4 18:00:57 2017. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. ABCE the Agent-Based Computational Economy platform that makes modeling easier ////////////////////////////////////////////////////////////////////////////// ABCE is a Python based modeling platform for economic simulations. ABCE comes with standard functions to simulations of trade, production and consumption. The modeler can concentrate on implementing the logic and decisions of an agents; ABCE takes care of all exchange of goods and production and consumption. .. figure:: cheesegrater.png :figwidth: 50 % :align: right In ABCE goods have the physical properties of goods in reality in the sense that 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. 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 can be inherited from archetype classes (Firm or Household). The only not-so-standard Python is that agents are executed in parallel by the Simulation class (in start.py). ABCE allows the modeler to program agents as ordinary Python class-objects, but run the simulation on a multi-core/processor computer. It takes no effort or intervention from the modeler to run the simulation on a multi-core system. The speed advantages of using ABCE with multi-processes enabled. ABCE are typically only observed for 10000 agents and more. Below, it might be slower than pure python implementation. ABCE supports pypy3, which is approximately 10 times faster than CPython. ABCE is a scheduler [#scheduler]_ and a set of agent classes. According to the schedule the simulation class calls - each sub-round - agents to execute some actions. Each agent executes these actions using some of the build-in functions, such as trade, production and consumption of ABCE. The agents can use the full set of commands of the Python general purpose language. The audience of ABCE are economists that want to model agent-based models of trade and production. ABCE does support an accounting framework for financial simulations. `ESL can be downloaded here `_. ABCE runs on macOS, Windows, and Linux. ABCE runs 10x faster on pypy! Introduction ============ .. toctree:: :maxdepth: 2 introduction installation jupyter_tutorial Walk_through tutorial examples unit_testing Simulation Programming ====================== .. toctree:: :maxdepth: 1 simulation Agent_class Goods Trade Messaging Firm Household Database notenoughgoods Advanced ======== .. toctree:: :maxdepth: 1 Contracting Quote spatial plugins Graphical User Interface and Results ==================================== .. toctree:: :maxdepth: 1 gui deploy Frequently asked Questions ========================== .. toctree:: :maxdepth: 1 faq Indices and tables ================== * :ref:`genindex` * :ref:`modindex` * :ref:`search` .. [#scheduler] the Simulation class .. [#noeq] with out the equilibrium of course