Artificial life

Artificial Life, also called ALife, is a special area of research where scientists study living things and how they change over time. They do this by using computer programs, robots, and experiments with tiny parts of living material. This field was started by a computer scientist named Christopher Langton in 1986, and he held the first meeting about it in Los Alamos, New Mexico, in 1987.

There are three main ways scientists create artificial life. One way uses computer software, called "soft" artificial life. Another uses real machines and tools, called "hard" artificial life. The third uses experiments with biological materials, called "wet" artificial life. By creating these models, scientists can learn more about how real living things work and develop.

Overview

Artificial life is a special kind of study where scientists look at how living things work by creating fake versions of them with computers and robots. This helps us understand more about life and how it changes over time. Researchers often study how groups of living things work together, copy nature in new ways, and think about big questions like what life really means. They also use ideas from life to make interesting art.

Philosophy

The philosophy behind artificial life is different from regular ways we study life. Instead of just looking at life as we know it, this field explores what life could be like in other ways.

Traditional models of living things focus on the most important details. But artificial life tries to find the simplest and most general ideas about life and put them into a computer program. This lets scientists study new and different kinds of life.

One big goal in artificial life is to create Open-Ended Evolution (OEE). This means making a system that can always create new, complex behaviors or creatures, without stopping or reaching a final point. Right now, most artificial life programs are not considered truly alive, but scientists have different ideas about what artificial life could become.

Software-based ("soft")

Techniques

Cellular automata have been used since the early days of artificial life and are still popular because they are easy to scale and run in parallel. Artificial neural networks are sometimes used to model the brain of an agent. Though they are usually part of artificial intelligence, neural networks can help simulate how groups of organisms change over time, especially those that can learn. The connection between learning and evolution is important for understanding how more complex instincts develop in organisms.

Program-based simulations use a "genome" language, often in the form of a computer program, instead of real biological DNA. These organisms "live" when their code runs, and they can copy themselves. Changes, or mutations, happen when the code is altered randomly. Cellular automata are often used but not always required. Another example includes artificial intelligence and multi-agent systems.

In module-based simulations, individual parts are added to a creature, changing its behaviors and traits either directly or through how the parts interact. These simulations focus more on letting users create and access the simulation rather than on mutation and evolution.

Parameter-based simulations use pre-set behaviors controlled by numbers or other fixed values that can change. Each organism has a set of numbers that control different aspects of its behavior.

Neural net-based simulations use neural networks to let creatures learn and develop. The focus is usually on learning rather than natural selection.

Complex systems modeling

Mathematical models of complex systems come in three types: black-box, white-box, and grey-box. Black-box models do not show the inner workings of a system, so you cannot see how smaller parts interact. White-box models show all the inner mechanisms clearly. Grey-box models are a mix of the two.

Creating a white-box model needs a good understanding of the subject before you start. Cellular automata are needed but not enough on their own. A white-box model is built using logical rules and basic principles to create detailed knowledge about how the system works.

Notable simulators

This is a list of artificial life and digital organism simulators:

Hardware-based ("hard")

Further information: Robot

Hardware-based artificial life mainly includes robots, which are machines that can guide themselves and perform tasks without someone telling them what to do at every step. These robots act automatically, like guided machines that can work on their own.

Biochemical-based ("wet")

Further information: Artificial cell, Synthetic biology, and Xenobiology

Biochemical-based life is studied in the field of synthetic biology. This type of research includes creating synthetic DNA. The word "wet" comes from the term "wetware". Scientists working on "wet" artificial life try to build simple living cells from bacteria called Mycoplasma laboratorium and also work on making cell-like systems from non-living materials.

In May 2019, scientists made an important step by changing a type of bacteria called Escherichia coli. They reduced the number of building blocks in its genome from 64 to 59, which helped them study how life works at a very tiny level.

In 2020, researchers created a biological robot with help from artificial intelligence. In 2021, the same group announced an amazing discovery: they made the first biological robots that could make copies of themselves. These robots gather cells from their surroundings to build new versions of themselves, which is something usually only seen in very small parts of life.

Open problems

Scientists studying artificial life have many big questions they are still trying to answer. One big question is how life can start from things that aren’t alive. They want to create simple living-like structures in labs and on computers, and learn if new kinds of living things are possible. They also want to simulate a single-celled organism throughout its whole life and understand how living things turn physical actions into rules and symbols.

Another question is about the possibilities and limits of living systems. Researchers are curious about what will always happen as life continues to evolve, and what the simplest conditions are for big changes in evolution. They aim to create a system that can organize itself at many different sizes, predict what will happen when we change organisms or ecosystems, and develop ideas about how information works and changes in evolving systems.

Finally, they wonder how life connects to thinking, machines, and culture. They want to show how intelligence and thinking can arise in artificial living systems, study how machines might affect the future of life’s evolution, and create models showing how culture and biology affect each other. They also want to create ethical rules for working with artificial life.

Related subjects

Agent-based modeling is a way to study how complex behaviors can arise in systems. Artificial intelligence often starts with big ideas, while artificial life looks at how simple rules can lead to more complex behaviors.

Artificial chemistry is a method used in artificial life to mimic how chemicals react. Evolutionary algorithms are tools that use ideas from artificial life to solve problems, like finding the best way to complete a task. These include methods like ant colony optimization, bacterial colony optimization, genetic algorithms, genetic programming, and swarm intelligence. Multi-agent systems are computer systems made up of many smart agents that interact with each other. Techniques from artificial life are also used in evolutionary art and evolutionary music to create new kinds of art and music. The study of how life began can also use artificial life methods. Quantum artificial life uses quantum computing to explore life-like systems.

History

Main article: History of artificial life

Artificial Life, often called ALife, is a field where scientists study how living things work and change. They use computers, robots, and special chemistry to create models that act like real life. The idea was started by a computer expert named Christopher Langton from the United States in 1986. One year later, in 1987, Langton brought together the first meeting about this exciting topic in Los Alamos, New Mexico.

Criticism

Some people have questioned the ideas behind artificial life. In 1994, a scientist named John Maynard Smith said that some work in this area was not based on real facts. Another thinker, Mario Bunge, argued that some beliefs about artificial life mix up the difference between a computer model and the real processes it tries to copy. However, he did not have the same concerns about other kinds of artificial life studies.