Ant Simulator – This is far more than just a game

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I have declared via AppNee platform: I myself do not have any human idols, all my adoring and admiring come from the world, the nature, the earth. Among them, the ant already existed on earth about 130 million years ago, and the world’s known classified species of ants have up to 22000 at present. If you are a fan of ants, then you must have found almost every available ant related games at AppNee.

Ant Simulator is not just another ant simulation game, but a feature-completed and interactive scientific program (education software) for learning or visualizing various ant behaviors on Windows and Mac OS X. It’s specially designed for researchers, students and children aged 8-12, developed by Glass Games Studios from China in 2016, and not ETeeski’s rotten and cancelled work with the same project name.

Ant Simulator is able to simulate various behaviors of ants for related scientific researches by providing different parameters that can be modified and affect ant behaviors in real time, as well as the detailed real-time statistics reporting and simulation data. In Ant Simulator, you can observe how they go out foraging, how they fight, how to defense, how to deal with the changes of weather and environment, how their complex and varied social systems evolve, and so on. At the same time, as an all-purpose educational software, Ant Simulator enables students or ants enthusiasts to learn about the ant’s daily life inside and around the nest in depth.

Although each ant can only perform some very simple actions, the accumulation of quantity necessarily leads to a qualitative leap. In other words, when the simple behaviors of a swarm of ants join up, this complex collective behavior is going to produce a completely different result – to solve the incredible problems more intelligently and efficiently. Scientists are able to utilize these research achievements to solve or improve various difficult or urgent problems existing in our human society. For example: biodiversity and conservation, machine learning, stochasticity of encounter and interaction networks, parallel computing, and other computing fields.

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