Artificial life (commonly Alife or alife) is a field of study and an associated art form which examine systems System is a set of interacting or interdependent entities forming an integrated whole related to life Life is a characteristic that distinguishes objects that have signaling and self-sustaining processes (biology) from those that do not, either because such functions have ceased (death), or else because they lack such functions and are classified as inanimate, its processes, and its evolution through simulations Simulation is used in many contexts, including the modeling of natural systems or human systems in order to gain insight into their functioning. Other contexts include simulation of technology for performance optimization, safety engineering, testing, training and education. Simulation can be used to show the eventual real effects of alternative using computer models A computer simulation, a computer model, or a computational model is a computer program, or network of computers, that attempts to simulate an abstract model of a particular system. Computer simulations have become a useful part of mathematical modeling of many natural systems in physics , astrophysics, chemistry and biology, human systems in, robotics Robotics is the engineering science and technology of robots, and their design, manufacture, application, and structural disposition. Robotics is related to electronics, mechanics, and software. The word robot was introduced to the public by Czech writer Karel Čapek in his play R.U.R. , published in 1920. The term "robotics" was coined, and biochemistry Biochemistry is the study of the chemical processes in living organisms. It deals with the structures and functions of cellular components such as proteins, carbohydrates, lipids, nucleic acids and other biomolecules. Over the last 40 years biochemistry has become so successful at explaining living processes that now almost all areas of the life.^[1] The discipline was named by Christopher Langton Christopher Langton is an American computer scientist and one of the founders of the field of artificial life. He coined the term in the late 1980s when he organized the first "International Conference on the Synthesis and Simulation of Living Systems" (otherwise known as Artificial Life I) at the Los Alamos National Laboratory in 1987, an American computer scientist, in 1986.^[2] There are three main kinds of alife^[3], named for their approaches: soft^[4], from software Computer software, or just software, is the collection of computer programs and related data that provide the instructions telling a computer what to do. The term was coined to contrast to the old term hardware . In contrast to hardware, software is intangible, meaning it "cannot be touched". Software is also sometimes used in a more; hard^[5], from hardware Hardware is a general term for the physical artifacts of a technology. It may also mean the physical components of a computer system, in the form of computer hardware; and wet Wet alife is artificial life created in vitro as opposed to the normally implied in silico when using the broader term alife. Generally wet alife involves experiments with chemical substrates in water or another solvent, from biochemistry. Artificial life imitates traditional biology Biology is a natural science concerned with the study of life and living organisms, including their structure, function, growth, origin, evolution, distribution, and taxonomy by trying to recreate biological phenomena.^[6] The term "artificial life" is often used to specifically refer to soft alife.^[7]

Overview

Artificial life studies the logic of living systems Living systems theory is a general theory about the existence of all living systems, their structure, interaction, behavior and development. This work is created by James Grier Miller, which was intended to formalize the concept of life. According to Miller's original conception as spelled out in his magnum opus Living Systems, a "living in artificial environments. The goal is to study the phenomena of living systems in order to come to an understanding of the complex information processing that defines such systems.

Also sometimes included in the umbrella term Artificial Life are agent based systems An agent-based model (also sometimes related to the term multi-agent system or multi-agent simulation) is a class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole. It which are used to study the emergent properties of societies of agents.

While artificial life is, by definition, alive, artificial life is generally referred to as being confined to a digital environment and existence.

Philosophy

The modeling philosophy of alife strongly differs from traditional modeling, by studying not only “life-as-we-know-it”, but also “life-as-it-might-be” ^[8].

In the first approach, 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, different life-like systems.

Red'ko proposed to generalize this distinction to not just to the modeling of life, but to any process. This led to the more general distinction of "processes-as-we-know-them" and "processes-as-they-could-be" ^[9]

At present, the commonly accepted definition of life Life is a characteristic that distinguishes objects that have signaling and self-sustaining processes (biology) from those that do not, either because such functions have ceased (death), or else because they lack such functions and are classified as inanimate does not consider any current alife simulations or softwares Computer software, or just software, is the collection of computer programs and related data that provide the instructions telling a computer what to do. The term was coined to contrast to the old term hardware . In contrast to hardware, software is intangible, meaning it "cannot be touched". Software is also sometimes used in a more to be alive, and they do not constitute part of the evolutionary process of any ecosystem An ecosystem consists of all the organisms living in a particular area, as well as all the nonliving, physical components of the environment with which the organisms interact, such as air, soil, water, and sunlight. It is all the organisms in a given area, along with the nonliving factors with which they interact; a biological community and its. However, different opinions about artificial life's potential have arisen:

• The strong alife (cf. Strong AI These three questions reflect the divergent interests of AI researchers, philosophers and cognitive scientists respectively. The answers to these questions depend on how one defines "intelligence" or "consciousness" and exactly which "machines" are under discussion) position states that "life is a process which can be abstracted away from any particular medium" (John von Neumann John von Neumann was a Hungarian-American mathematician who made major contributions to a vast range of fields, including set theory, functional analysis, quantum mechanics, ergodic theory, continuous geometry, economics and game theory, computer science, numerical analysis, hydrodynamics (of explosions), and statistics, as well as many other). Notably, Tom Ray declared that his program Tierra is not simulating life in a computer but synthesizing it.

• The weak alife position denies the possibility of generating a "living process" outside of a chemical solution. Its researchers try instead to simulate life processes to understand the underlying mechanics of biological phenomena.

Organizations

Software-based - "soft"

Techniques

• Cellular automata A cellular automaton is a discrete model studied in computability theory, mathematics, physics, complexity science, theoretical biology and microstructure modeling. It consists of a regular grid of cells, each in one of a finite number of states, such as "On" and "Off" (in contrast to a coupled map lattice). The grid can be in were used in the early days of artificial life, and they are still often used for ease of scalability and parallelization. Alife and cellular automata share a closely tied history.

• Neural networks Traditionally, the term neural network had been used to refer to a network or circuit of biological neurons[citation needed]. The modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes. Thus the term has two distinct usages: are sometimes used to model the brain of an agent. Although traditionally more of an artificial intelligence Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as "the study and design of intelligent agents," where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who technique, neural nets can be important for simulating population dynamics of organisms that can learn. The symbiosis between learning and evolution is central to theories about the development of instincts in organisms with higher neurological complexity, as in, for instance, the Baldwin effect The Baldwin effect, also known as Baldwinian evolution or ontogenic evolution, is an early evolutionary theory put forward in 1896 in a paper "A New Factor in Evolution" by American psychologist James Mark Baldwin which proposes a mechanism for specific selection for general learning ability. Selected offspring would tend to have an.

Notable simulators

This is a list of Artificial life/Digital organism A digital organism is a self-replicating computer program that mutates and evolves. Digital organisms are used as a tool to study the dynamics of Darwinian evolution, and to test or verify specific hypotheses or mathematical models of evolution. This is closely related to the area of artificial life simulators, organized by the method of creature definition.

Program-based

These contain organisms with a complex DNA language, usually Turing complete In computability theory, a collection of data-manipulation rules is said to be Turing complete if and only if such system can simulate a single-taped Turing Machine. Classical Turing-complete systems include context-dependent grammars, recursive functions and lambda calculus. This language is more often in the form of a computer program than actual biological DNA. Assembly derivatives are the most common languages used. Use of cellular automata A cellular automaton is a discrete model studied in computability theory, mathematics, physics, theoretical biology and microstructure modeling. It consists of a regular grid of cells, each in one of a finite number of states, such as "On" and "Off". The grid can be in any finite number of dimensions. For each cell, a set of is common but not required.

• Tierra (early 1990s)
• Avida Avida is an artificial life software platform to study the evolutionary biology of self-replicating and evolving computer programs . Avida is under active development by Charles Ofria's Digital Evolution Lab at Michigan State University and was originally designed by Ofria, Chris Adami and C. Titus Brown at Caltech in 1993. The software was (1993-present)
• Evolve 4.0 (1996–2007)
• Darwinbots DarwinBots is an open source artificial life simulator, originally developed by Carlo Comis, providing a virtual environment in which a number of digital organisms called "bots" interact, fight for resources, and eventually reproduce and evolve (2003–2008)
• Framsticks Framsticks is a 3D freeware Artificial Life simulator. Organisms consisting of physical structures and control structures ("brains") evolve over time against a user's predefined fitness landscape (for instance, evolving for speed) (1996–present)
• breve breve is a free, GPL software package that makes it easy to build 3D simulations of decentralized systems and artificial life. Users can define the behaviors of multi-agent systems in a 3D world and observe how they interact, a multi-purpose simulation environment (2006–present)
• DigiHive (2006–2009)

Module-based

Individual modules are added to a creature. These modules modify the creature's behaviors and characteristics either directly, by hard coding into the simulation (leg type A increases speed and metabolism), or indirectly, through the emergent interactions between a creature's modules (leg type A moves up and down with a frequency of X, which interacts with other legs to create motion). Generally these are simulators which emphasize user creation and accessibility over mutation and evolution.

• TechnoSphere TechnoSphere was an online digital environment launched on September 1, 1995 and hosted on a computer at a UK university. TechnoSphere, created by Jane Prophet and Gordon Selley, was a place where users from around the globe could create creatures and release them into the 3D environment, described by the creators as a "digital ecology."

Parameter-based

Organisms are generally constructed with pre-defined and fixed behaviors that are controlled by various parameters that mutate. That is, each organism contains a collection of numbers or other finite parameters. Each parameter controls one or several aspects of an organism in a well-defined way.

• Kyresoo Plants

Neural net–based

These simulations have creatures that learn and grow using neural nets or a close derivative. Emphasis is often, although not always, more on learning than on natural selection.

• Creatures Creatures is an artificial life computer program series, created in the mid-1990s by English computer scientist Steve Grand whilst working for the Cambridge computer games developer Millennium Interactive. The program is one of the few games (as of 2008) to employ machine learning (a game)
• Noble Ape
• Polyworld

Hardware-based - "hard"

Hardware-based artificial life mainly consist of robots, that is, automatically Automation is the use of control systems and information technologies reducing the need for human intervention. In the scope of industrialization, automation is a step beyond mechanization. Whereas mechanization provided human operators with machinery to assist them with the muscular requirements of work, automation greatly reduces the need for guided machines A machine is a device that uses energy to perform some activity. In common usage, the meaning is that of a device having parts that perform or assist in performing any type of work. A simple machine is a device that transforms the direction or magnitude of a force without consuming any energy. The word "machine" is derived from the Latin, able to do tasks on their own.

Biochemical-based - "wet"

Biochemical-based life is studied in the field of synthetic biology Synthetic biology is a new area of biological research that combines science and engineering. Synthetic biology encompasses a variety of different approaches, methodologies and disciplines, and many different definitions exist. What they all have in common, however, is that they see synthetic biology as the design and construction of new. It involves e.g. the creation of synthetic DNA. The term "wet" is an extension of the term "wetware".

Related subjects

1. Artificial intelligence Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as "the study and design of intelligent agents," where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who has traditionally used a top down approach, while alife generally works from the bottom up.^[10]
2. Artificial chemistry An artificial chemistry is a computer model used to simulate various types of systems. Artificial chemistry is in some ways similar to a chemical reaction, hence the name. The field of artificial chemistry originated in artificial life but has shown to be a versatile method with applications in many fields such as chemistry, economics, sociology started as a method within the alife community to abstract the processes of chemical reactions.
3. Evolutionary algorithms In artificial intelligence, an evolutionary algorithm is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses some mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of are a practical application of the weak alife principle applied to optimization problems In mathematics and computer science, an optimization problem is the problem of finding the best solution from all feasible solutions. More formally, an optimization problem A is a quadruple , where. Many optimization algorithms have been crafted which borrow from or closely mirror alife techniques. The primary difference lies in explicitly defining the fitness of an agent by its ability to solve a problem, instead of its ability to find food, reproduce, or avoid death.^{[citation needed]} The following is a list of evolutionary algorithms closely related to and used in alife:
   • Ant colony optimization The ant colony optimization algorithm , is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs
   • Evolutionary algorithm In artificial intelligence, an evolutionary algorithm is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses some mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of
   • Genetic algorithm The genetic algorithm is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by
   • Genetic programming In artificial intelligence, genetic programming is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. It is a specialization of genetic algorithms (GA) where each individual is a computer program. It is a machine learning technique used to optimize a population
   • Swarm intelligence Swarm intelligence is a type of artificial intelligence based on the collective behavior of decentralized, self-organized systems. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems
4. Evolutionary art In common with natural selection and animal husbandry, the members of a population undergoing artificial evolution modify their form or behavior over many reproductive generations in response to a selective regime uses techniques and methods from artificial life to create new forms of art.
5. Evolutionary music uses similar techniques, but applied to music instead of visual art.

History

Criticism

Alife has had a controversial history. John Maynard Smith John Maynard Smith, F.R.S. was a British theoretical evolutionary biologist and geneticist. Originally an aeronautical engineer during the Second World War, he then took a second degree in genetics under the well-known biologist J.B.S. Haldane. Maynard Smith was instrumental in the application of game theory to evolution and theorized on other criticized certain artificial life work in 1994 as "fact-free science".^[11] However, the recent publication of artificial life articles in widely read journals such as Science and Nature is evidence that artificial life techniques are becoming more accepted in the mainstream, at least as a method of studying evolution.^[12]

See also

• Autonomous foraging
• Artificial life organizations
• Bioethics
• Complex adaptive system
• Darwin machine
• Digital morphogenesis
• Life simulation game
• Mathematical biology
• Player Project
• Social simulation
• Soda Constructor
• Synthetic life
• Webots
• bugsx

References

1. ^ "Dictionary.com definition". http://dictionary.reference.com/browse/artificial%20life. Retrieved 2007-01-19.
2. ^ The MIT Encyclopedia of the Cognitive Sciences, The MIT Press, p.37. ISBN 978-0262731447
3. ^ Mark A. Bedau (November 2003). "Artificial life: organization, adaptation and complexity from the bottom up" (PDF). TRENDS in Cognitive Sciences. http://www.reed.edu/~mab/publications/papers/BedauTICS03.pdf. Retrieved 2007-01-19.
4. ^ Maciej Komosinski and Andrew Adamatzky (2009). Artificial Life Models in Software. New York: Springer. ISBN 978-1-84882-284-9. http://www.springer.com/computer/mathematics/book/978-1-84882-284-9.
5. ^ Andrew Adamatzky and Maciej Komosinski (2009). Artificial Life Models in Hardware. New York: Springer. ISBN 978-1-84882-529-1. http://www.springer.com/computer/hardware/book/978-1-84882-529-1.
6. ^ Christopher Langton. "What is Artificial Life?". http://zooland.alife.org/. Retrieved 2007-01-19.
7. ^ John Johnston, (2008) "The Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI", MIT Press
8. ^ See Langton, C. G. 1992. Artificial Life. Addison-Wesley. ., section 1
9. ^ See Red'ko, V. G. 1999. Mathematical Modeling of Evolution. in: F. Heylighen, C. Joslyn and V. Turchin (editors): Principia Cybernetica Web (Principia Cybernetica, Brussels). For the importance of ALife modeling from a cosmic perspective, see also Vidal, C. 2008.The Future of Scientific Simulations: from Artificial Life to Artificial Cosmogenesis. In Death And Anti-Death , ed. Charles Tandy, 6: Thirty Years After Kurt Gödel (1906-1978) p. 285-318. Ria University Press.)
10. ^ "AI Beyond Computer Games". http://lggwg.com/wolff/aicg99/stern.html. Retrieved 2008-07-04.
11. ^ Horgan, J. 1995. From Complexity to Perplexity. Scientific American. p107
12. ^ "Evolution experiments with digital organisms". http://myxo.css.msu.edu/cgi-bin/lenski/prefman.pl?group=al. Retrieved 2007-01-19.

External links

• Computers: Artificial Life at the open directory project
• Computers: Artificial Life Framework
• International Society of Artificial Life
• Artificial Life MIT Press Journal
• The Artificial Life Lab Envirtech Island, Second Life

Categories: Artificial life | Scientific modeling

See Also:

What Links Here:

Recently Viewed Pages:

• Home
• Esperanto: Blogs
• Geber: News
• List of Latinised Names: Blogs
• Speech Communication: Blogs
• Double Dutch: Blogs
• List of Latinised Names: Encyclopedia
• Speech Communication: Encyclopedia
• Gibberish: Encyclopedia
• Science: Social Sciences: Linguistics: Languages: Constructed: Reformed and Modified English: Directory

Most Popular Pages:

• Geber: News
• Double Dutch: Blogs
• Double Dutch: Images
• Issue Life Cycle: Blogs
• Esperanto: Blogs
• Native Speakers: Blogs
• List of Latinised Names: Blogs
• Jabber
• Lojban: Blogs
• Gobbledegook: Blogs

Related 'Artificial Life' Searches: