Species: Artificial Life, Real Evolution Free Download
Lashawna Vorhees
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Play with evolution! Species: ALRE is a scientifically-grounded, emergent simulation of natural selection. Creatures evolve and speciate in response to in-game mutation and selection forces, allowing you to experience and tinker with evolution in real-time.
Hey there, gamers! Get ready to dive deep into the world of evolution with Species: Artificial Life, Real Evolution (ALRE for short). This game is like a mad scientist's playground, where you can unleash your inner Darwin and witness the magic of natural selection in action!
ALRE is not your average simulation game, folks. It's scientifically-grounded and super immersive, guaranteeing an experience like no other. Just imagine: creatures evolving and speciating right before your eyes, adapting to their environments, and battling it out for survival. It's like nature's version of "The Hunger Games" -- survival of the fittest, baby!
But that's not all! ALRE lets you be the ultimate puppeteer of evolution. You can unleash in-game mutations and manipulate the selection forces to see how the creatures react and evolve. It's like playing with real-life Sims, except instead of building houses, you're building an entire ecosystem. And trust me, it's addictive as heck.
Whether you want to test your knowledge of evolutionary theories or simply enjoy the spectacle of creatures evolving, Species: ALRE has got you covered. And let's not forget the stunning visuals that'll make your eyes pop. The graphics are so gorgeous, you'll forget you're actually, you know, playing a game.
So, if you're ready to step into the shoes of Mother Nature and witness the wonders of evolution unfold right before your very eyes, grab a copy of Species: ALRE and let the games begin! It's time to channel your inner GameGal and create the ultimate evolutionary masterpiece. Oh, and don't forget to share your creations because I know they'll be nothing short of mind-blowing! Let's go!
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Artificial life (ALife or A-Life) is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry.[1] The discipline was named by Christopher Langton, an American theoretical biologist, in 1986.[2] In 1987, Langton organized the first conference on the field, in Los Alamos, New Mexico.[3] There are three main kinds of alife,[4] named for their approaches: soft,[5] from software; hard,[6] from hardware; and wet, from biochemistry. Artificial life researchers study traditional biology by trying to recreate aspects of biological phenomena.[7][8]
Artificial life studies the fundamental processes of living systems in artificial environments in order to gain a deeper understanding of the complex information processing that define such systems. These topics are broad, but often include evolutionary dynamics, emergent properties of collective systems, biomimicry, as well as related issues about the philosophy of the nature of life and the use of lifelike properties in artistic works.[citation needed]
A traditional model of a biological system will focus on capturing its most important parameters. In contrast, an alife modeling approach will generally seek to decipher the most simple and general principles underlying life and implement them in a simulation. The simulation then offers the possibility to analyse new and different lifelike systems.
Vladimir Georgievich Red'ko proposed to generalize this distinction to the modeling of any process, leading to the more general distinction of "processes-as-we-know-them" and "processes-as-they-could-be".[10]
At present, the commonly accepted definition of life does not consider any current alife simulations or software to be alive, and they do not constitute part of the evolutionary process of any ecosystem. However, different opinions about artificial life's potential have arisen:
Program-based simulations contain organisms with a "genome" language. This language is more often in the form of a Turing complete computer program than actual biological DNA. Assembly derivatives are the most common languages used. An organism "lives" when its code is executed, and there are usually various methods allowing self-replication. Mutations are generally implemented as random changes to the code. Use of cellular automata is common but not required. Another example could be an artificial intelligence and multi-agent system/program.
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