What is artificial life?
Artificial life as defined by Christopher Langton
“Artificial Life is the study of man-made systems that exhibit behaviors characteristic of natural living systems. It complements the traditional biological sciences concerned with the analysis of living organisms by attempting to synthesize life-like behaviors within computers and other artificial media. By extending the empirical foundation upon which biology is based beyond the carbon-chain life that has evolved on Earth, Artificial Life can contribute to theoretical biology by locating life-as-we-know-it within the larger picture of life-as-it-could-be. – (Langton, 1989)”
Artificial life (also known as ‘ALife’) is an interdisciplinary study of life and life-like processes that uses a synthetic methodology, wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry.
Three broad and intertwining branches of artificial life correspond to three different synthetic methods.
- ‘Soft’ artificial life creates simulations or other purely digital constructions that exhibit life-like behavior.
- ‘Hard’ artificial life produces hardware implementations of life-like systems and
- ‘Wet’ artificial life} synthesizes living systems out of biochemical substances.
A-life research efforts are truly interdisciplinary and runs the gamut from biology, chemistry and physics to computer science and engineering. While a large part of Artificial Life is devoted to understanding life as we know it – that is, life on earth – a significant effort concerns the search for principles of living systems which are independent of a particular substrate. Thus, Artificial Life also considers life “as it could be”, exploring artificial alternatives to a carbon-based chemistry.
At present, this subfield is split into two largely independent endeavors:
- Creation of life using the classical building blocks of nature (carbon-based life) : Explores the possibility of “RNA worlds” by attempting to construct self-replicating molecules
- Creation of life using the same principles but a different medium for implementation : By simulating simple populations of self-replicating entities, examines the abilities and characteristics of different chemistry in supporting life-like behavior.
Thus, both the biochemical and the computational approaches seek to shed light on the compelling question of the origin of life.
Examples of Artificial life:
Artificial cells : Artificial cells are microscopic, autonomously self-organizing and self-replicating physical entities that assemble themselves out of non-living materials. Although artificial, they would repair themselves and adapt in an open-ended fashion, so for all intents and purposes they would be alive.
Artificial cell would help us understand the origin of life, how can life arise from non living substrates along with clear view of their evolutionary potential. The key properties that will help achieve the ALife goal are self-maintenance, autonomous control of chemical processing, autonomous control of mobility, and self-replication.
An artificial cell which is simpler than any existing in nature would help in studying the core functions of life, and allow us to work out the function of every gene that keeps it alive. That could yield insights into how genes can be re-purposed. It may provide understanding how a living cell works. More precisely it may help us unravel the essential toolkit of life, something that may be common to all free-living creatures on Earth, including humans.
ALife Research is pursuing two approaches.
- Venter and Smith are using the top-down strategy of artificially synthesizing and modifying the genome of the organism with the smallest genome, the bacterium Mycoplasma genitalium. The other approach is bottom-up, building more and more complex physiochemical systems that increasingly incorporate life-like properties.
In May 2010, a team of scientists led by Venter became the first to successfully create what was described as “synthetic life”. This was done by synthesizing a very long DNA molecule containing an entire bacterium genome, and introducing this into another cell, analogous to the accomplishment of Eckard Wimmer’s group, who synthesized and ligated an RNA virus genome and “booted” it in cell lysate. Scientists Create First Synthetic Cell – WSJInteresting there is lot the step with no doubt would be the corner-stone in the field, but has drawn many opposing the step as well. wondering why?
Easy “you create life you become god”, but are they life? Yes they are but we did not make them up from scratch, scientist has taken such steps in past like cloning and we end up with same question(being ethical is important but we like to explore) and next question was important for me what if we could contain and control such life, we human try to make things better always what is the Alife turn more advanced than us (feeling insecure, sounds like Sci-fi movie right)? These are challenges of innovation it comes with the packages. An interesting article to ready on this can be found here : Ethics concern over synthetic cell – BBC News – BBC.com
- Some bottom-up efforts are strongly inspired by the RNA chemistry in existing cells, whereas others pursue a simpler chemistry that replaces RNA with PNA (peptide nucleic acid, an analog of DNA in which the backbone is a pseudopeptide rather than a sugar).
Evolutionary Robotics :
Artificial Life is not only about the construction and simulation of living systems, whether artificial or natural; an impressive engineering effort is geared towards the construction of adaptive autonomous robots. This work differs from the classical robotics approach, in that the robotic agent interacts with its environment and learns from this interaction, leading to emergent robotic behavior. The ALife alternative is to follow nature and use an evolutionary design method.
Evolutionary robotics aim to examines different aspects of applied evolutionary algorithms, including Adaptive and social behaviour, morphology, control, perception and even self-* (self-adapting, self-assembling, self-repairing, etc). These aspects are responsible for the generation of order in nature. They involve components at different scales, such as molecules, cells and organisms.
Researcher across many disciplines believe that the study of physical models of even self*, morphology, control and perception can help in understanding nature and in advancing technology. Evolutionary robotics investigates life as “it could be”. It uses computer simulation to study even self* as a means by which intelligent composite entities form and exhibit properties of living beings such as growth, development, self-repair, reproduction. The entities would ultimately change through an evolutionary process and hence could be considered as novel forms of artificial life.
Much work at the multicellular level has occurred in ‘hard’ artificial life, which is concerned with various forms of autonomous agents such as robots. This is artificial life’s most direct overlap with cognitive science, as its aim is to synthesize autonomous adaptive and intelligent behavior in the real world. One of the tricks is to allow the physical environment to generating the behavior as far as possible. Traditional rational design for intelligent autonomous agents is difficult, because it involves sophisticated interconnections among many complex components.
There are many more example domain in artificial life-like the field of Evolutionary computing and swarms intelligence(Ant colony optimization, particle swarm optimization, genetic algorithm etc.), but I would like to discuss them for later. The two examples above are two side of the same coin trying to do the same things in two different approach to Alife, as described earlier.
Interesting question is what would we gain by stimulating life or creating a Alife?, here is what I understood and I think:
- Unravel the essential toolkit of “life-as-we-know-it” – that is, life on earth (carbon chain form of life) and living systems which are independent of a particular substrate -that is “life-as-it-could-be”.
- Artificial Life is often described as attempting to understand high-level behavior from low-level rules. For example, how the simple rules of Darwinian evolution lead to high-level structure, or the way in which the simple interactions between ants and their environment lead to complex trail-following behavior.
- Study of how evolution and neural networks can produce artificial brains capable of learning.
- How genetic information is expressed phenotypically, that is, which amino acids are produced, and evolution of the genetic code takes the form of changes in the enzymes used in amino-acid synthesis.
- How does an intelligent composite entity form and exhibits properties of living beings such as growth, development, self-repair, reproduction, social behavior, morphology, control, perception and even self-* (self-adapting, self-assembling, self-repairing, etc.
- How does a multi-cellular organization evolves, from simple to more complex as seen in nature.
- Understand aspects of language, including phonetics and phonology, language acquisition, language change, the evolution of signaling systems, the grounding of symbols and the evolution of meanings, the emergence of complex structured languages, and the co-evolution of languages and language learning mechanisms.
- Understand the social and adaptive behaviors of organism in groups how the structure and behavior of social groups arises and is controlled.
- Understand the natures way of exhibiting a variety of competitive and cooperative ecological relationships.
- Explain how robust, multiple-level dynamical hierarchies emerge solely from the interactions of elements at the lowest-level. Understanding this relationship in particular systems promises to provide novel solutions to complex real-world problems, such as disease prevention, stock-market prediction, and data-mining on the Internet.
- Even may help us understand the deep connections between consciousness, emotion, mind and brain.
In the upcoming post I would like to discuss on the challenges of Artificial life, I am always open to suggestion so if you have one you ae most welcomed.
Reference: Bedau, Mark A. “Artificial life: organization, adaptation and complexity from the bottom up.” Trends in cognitive sciences 7.11 (2003): 505-512.
Thanks to Dr. Alice ‘O Toole for selection of an interesting topic and guidance, my friends and class mates for the discussion on the topic which enabled me to dive deep into.