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![image](uploads/622e63f0b412accfa29ace4d3a5f14dc/image.png)
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![image](uploads/55ed6107f13ab21cf83ef7625af74c14/image.png)
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# Overview
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UMANS is an easy to use crowd simulation tool. It is aimed to be used by scientific community, without any specific programming knowledges.
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With UMANS, you can generate the trajectory of each agent of a crowd, by optimizing a cost function in a velocity space. UMANS can reproduce many types of local algorithms using a single general principle, which allows you to compare classical algorithms of crowd simulation.
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The environment and goals are voluntarily kept simple, to focus on local interactions between agents. UMANS **does not** implement global path planning.
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With UMANS, you can use many different cost functions and change their parameters as you wish. You can also create your own cost functions thanks to a generic architecture. You can also play with different optimisation methods.
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## Introduction
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[UMANS](https://project.inria.fr/crowdscience/project/ocsr/umans/) (short for Unified Microscopic Agent Navigation Simulator) is an easy to use crowd simulation engine that focuses on the local (a.k.a. "microscopic") aspects of navigation.
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Many algorithms for microscopic crowd simulation have been developed over the past decades. However, each implementation has its own settings and details that can greatly influence the results. The purpose of UMANS is to reproduce as many existing algorithms as possible via one principle, while unifying as many overall settings as possible. This allows for a more honest and meaningful comparison of simulation algorithms.
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UMANS was previously known as OCSR (Open Crowd Simulation Resources). Some parts of the project may still use this old name. Since 2020, the term "[OCSR](https://project.inria.fr/crowdscience/project/ocsr/)" refers to the collective of open crowd-simulation resources developed at Inria Rennes. These resources include UMANS (a simulation engine) and [ChAOS](https://project.inria.fr/crowdscience/project/ocsr/chaos/) (a visualization application).
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## Should you use UMANS ?
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UMANS is aimed to be used by scientific community, without any specific programming knowledges.
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With UMANS, you can generate the trajectory of each agent of a crowd: it can reproduce many types of local algorithms using a single general principle, which allows you to compare classical algorithms of crowd simulation.
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The environment and goals are voluntarily kept simple, to focus on local interactions between agents.
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UMANS **does not** implement global path planning.
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With UMANS, you can use many different cost functions and change their parameters as you wish.
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You can also create your own cost functions thanks to a generic architecture.
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You can also play with different optimisation methods, and create your own optimisation method.
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---------
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## [Installation and configuration]
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## Installation and configuration
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* [Configuration](Installation-and-configuration/Configuration)
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* [Installation](Installation-and-configuration/Installation)
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