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توضیحات

An Agent Based Modelling Engine tailored for Reinforcement Learning.

ویژگی	مقدار
سیستم عامل	-
نام فایل	adjsim-2.1.0
نام	adjsim
نسخه کتابخانه	2.1.0
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Sever Topan
ایمیل نویسنده	-
آدرس صفحه اصلی	https://github.com/SeverTopan/AdjSim
آدرس اینترنتی	https://pypi.org/project/adjsim/
مجوز	GPL-3.0

AdjSim Simulation Framework =========================== |Build Status| |Coverage Status| |License: GPL v3| Designed and developed by Sever Topan Navigation ---------- 1. `Feature Abstract <#Features>`__ 2. `Installation Instructions <INSTALL.md>`__ 3. `Tutorial <tutorial/tutorial.ipynb>`__ 4. `Class Documentation <https://severtopan.github.io/AdjSim/>`__ Features -------- Engine ~~~~~~ At its core, AdjSim is an agent-based modelling engine. It allows users to define simulation environments through which agents interact through ability casting and timestep iteration. The framework is targeted towards agents that behave intelligently, for example a bacterium chasing down food. However, the framework is extremely flexible - from enabling physics simulation to defining an environment in which `Conway's Game of Life <https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life>`__ plays out! AdjSim aims to be a foundational architecture on top of which reinforcement learning can be built. Graphical Simulation Representation ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The simulation can be viewed in real time as it unfolds, with graphics are rendered and animated using PyQt5. Below are four of the distinct examples packadged with AdjSim, ranging from bacteria to moon system simulation. +-------------------+------------------------+ | |Bacteria Demo| | |Predator Prey Demo| | +===================+========================+ | |GOL Demo| | |Jupiter Demo| | +-------------------+------------------------+ Post Simulation Analysis Tools ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Agent properties can be marked for tracking during simulation, allowing for viewing the results of these values once the simulation completes. For example, we can track the population of each different type of agent, or the efficacy of the agent's ability to meet its intelligence module-defined goals. \| |QLearning Graph|\ \| |Predator Prey Graph| \| \|:-------------:\|:-------------:\| Intelligence Module ~~~~~~~~~~~~~~~~~~~ Perhaps the most computationally interesting aspect of AdjSim lies in its intelligence module. It allows agents to set goals (for example, the goal of a bacterium may be to maximize its calories), and assess its actions in terms of its ability to meet its goals. This allows the agents to learn which actions are best used in a given situation. Currently the intelligence module implements `Q-Learning <https://en.wikipedia.org/wiki/Q-learning>`__, but more advanced reinforcement learning techniques are coming soon! .. |Build Status| image:: https://travis-ci.org/SeverTopan/AdjSim.svg?branch=master :target: https://travis-ci.org/SeverTopan/AdjSim .. |Coverage Status| image:: https://coveralls.io/repos/github/SeverTopan/AdjSim/badge.svg?branch=master :target: https://coveralls.io/github/SeverTopan/AdjSim?branch=master .. |License: GPL v3| image:: https://img.shields.io/badge/License-GPL%20v3-blue.svg :target: https://www.gnu.org/licenses/gpl-3.0 .. |Bacteria Demo| image:: https://raw.githubusercontent.com/SeverTopan/AdjSim/master/gallery/images/readme_bacteria.png .. |Predator Prey Demo| image:: https://raw.githubusercontent.com/SeverTopan/AdjSim/master/gallery/images/readme_predator_prey.png .. |GOL Demo| image:: https://raw.githubusercontent.com/SeverTopan/AdjSim/master/gallery/images/readme_game_of_life.png .. |Jupiter Demo| image:: https://raw.githubusercontent.com/SeverTopan/AdjSim/master/gallery/images/readme_jupiter_moon_system.png .. |QLearning Graph| image:: https://raw.githubusercontent.com/SeverTopan/AdjSim/master/gallery/images/readme_individual_learning.png .. |Predator Prey Graph| image:: https://raw.githubusercontent.com/SeverTopan/AdjSim/master/gallery/images/readme_predator_prey_population.png

نیازمندی

مقدار	نام
==5.9	PyQt5
==2.0	matplotlib
==1.13	numpy

زبان مورد نیاز

مقدار	نام
>=3.5, <3.7	Python

نحوه نصب

نصب پکیج whl adjsim-2.1.0:

pip install adjsim-2.1.0.whl

نصب پکیج tar.gz adjsim-2.1.0:

pip install adjsim-2.1.0.tar.gz