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Artificial Life
"If you're looking for a role model in a world of complexity, you could do worse than to imitate a bee." Artificial life has its roots in the fertile landscapes of biology and computer science. Known to many as 'AL' or 'Alife', this branch of science seeks to cultivate synthetic, life-like behaviors such as growth, adaptation, reproduction, socialization, learning, and even death. Not being confined to the recipe of our primordial soup, Alife scientists can utilize synthetic ingredients, computer programs that compress time, and other wondrous technologies as they seek to generate neomorphic behaviors and incarnations. Yet the answer to the question "At what point can something be deemed to be a form of artificial life?", is much like beauty: it's often in the eye of the beholder. And somewhat related to this is the caveat that whether something is 'natural' or 'artificial' may well be relative to one's vantage point ! The resources listed below will introduce you to such marvels as computer-based neural networks that resemble their real-life counterparts; computer viruses that behave like organic viruses; genetic and evolutionary algorithms that harness the strategies of life and apply them to problem solving; bots that travel the internet sharing information and helping each other; and robots that will create their own next generation. Good Places to StartWhat is Artificial Life? By Chris G. Langton. From the Zooland site. "Artificial life amounts to the practice of 'synthetic biology' and, by analogy with synthetic chemistry, the attempt to recreate biological phenomena in alternative media will result in not only better theoretical understanding of the phenomena under study, but also in practical applications of biological principles in the technology of computer hardware and software, mobile robots, spacecraft, medicine, nanotechnology, industrial fabrication and assembly, and other vital engineering projects." Artificial Life. Chapter Six of the Artificial Intelligence Tutorial Review, developed and compiled by Eyal Reingold and Johnathan Nightingale at the the University of Toronto. "Artificial Life relates to Biology in much the same fashion that Artificial Intelligence relates to Psychology. The goal of artificial life, or ALife, is to provide a different focus for researchers in biology. Rather than emphasize an analytic approach - attempting to understand the complex phenomena of life by breaking them down into simpler units - ALife offers a synthetic perspective - it begins with simple rules and concepts, and combines them to see what complex phenomena are produced." Scientific American Frontiers with Alan Alda: Robot Independence segment from the Life's Really Big Questions television broadcast (December 19, 2000). "Natural selection is at work in the artificial world, as robots learn to reproduce without us." The relationship between matter and life. By Rodney Brooks. Nature 409, 409 - 411 (2001). "Researchers in artificial intelligence (AI) and artificial life (Alife) are interested in understanding the properties of living organisms so that they can build artificial systems that exhibit these properties for useful purposes. AI researchers are interested mostly in perception, cognition and generation of action, whereas Alife focuses on evolution, reproduction, morphogenesis and metabolism. Neither of these disciplines is a conventional science; rather, they are a mixture of science and engineering. Despite, or perhaps because of, this hybrid structure, both disciplines have been very successful and our world is full of their products."
Artificial Life FAQs. "This document is intended to serve as an immediate resource for the readers of the newsgroup comp.ai.alife. It is intended to be lightweight; for more detailed information, follow the references." Maintained by Titus Brown. It's life, but not as we know it. By Beverley Head. The Sydney Morning Herald (November 29, 2005). "Ten years ago it took an hour to fly from Melbourne to Sydney. Now it's an hour and a half. 'That's not because the planes got slower, it's because of air-traffic control,' says Professor Peter Lindsay, director of the Australian Research Council's Centre for Complex Systems. He believes that if aircraft can be made to flock, similar to birds, it would drastically improve air-traffic management. Professor Lindsay, who holds the Boeing chair of systems engineering at the University of Queensland, is one of a growing number of computer scientists using the real world as muse and laboratory. They are forming multidisciplinary teams to look into how complex systems such as networks and traffic management are tackled in the real world. It is hoped that industry - which shows little interest in the science - will use the findings to make new computer systems that solve highly complex problems. 'We're looking at how birds flock through swarm analysis,' Professor Lindsay says. 'The artificial-life people have a good idea of how they do it. This will help develop a new model for air-traffic management.'"
What is Artificial Life? By Chris Adami and Titus Brown. From the Seventh International Conference on Artificial Life web site. "Yet 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." Guide to Artificial Life. Stewart Dean's primer. As stated in the Introduction: "Artificial Life, increasingly called aLife by its disciples, is about the emergent properties. An emergent property is created when something becomes more than the sum of its parts." AI and Alife: Notes in response to a journalist's request for an overview. (Last updated: August 10, 1998) From Aaron Sloman's collection of online interviews. "Even though each of AI and Alife subsumes the other, the differences in emphasis, and in level of description are real enough." Artificial Life for Computer Graphics. By Demetri Terzopoulos. Communications of the ACM 42(8): August 1999, pages 33 - 42. [The article is available from the author's Visual Modeling Showcase: Artificial Life.] "At the apex of the modeling pyramid, cognitive modeling has emerged as the use of artificial intelligence techniques, including knowledge representation, reasoning, and planning, to produce graphical characters with some level of deliberative intelligence and free will. ALife modeling spans the biomechanical-to-cognitive layers of the pyramid and investigates the possibility of applying evolutionary models to evolve graphical characters or aspects of their bodies and brains." - from Figure 1: Artificial life modeling and the computer graphic animation modeling hierarchy.
Readings OnlineArtificial Life - the official journal of the International Society of Artificial Life (ISAL) published by the MIT Press.
Artificial Life. "In this issue of Crossroads [Winter 2001], we delve into this fascinating, albeit nascent field. Our investigation begins with Cory Quammen's research on evolutionary learning in mobile robot navigation. ... Tony Belpaeme and Andreas Birk follow by describing the state of the art in animat research.... To conclude this issue, we chose Marco Grubert's captivating interdisciplinary investigation of simulated plant growth." -from Bill Stevenson's Introduction. Biological robotics - Working out the bugs. Programming a robot to think like an insect is tough but it could help breed machines as manoeuvrable as flies. By Alison Abbott. news @ nature.com (January 17, 2007). "Tarry II looks like a robot, sounds like a robot, and walks like an insect. He sprouts a tangle of wires, and the mechanical joints on his six legs emit a metallic creak with every step. But he strides determinedly across the lab with the steady gait of a fly marching towards rotting fruit. The strutting machine is the work of Roland Strauss at the University of Würzburg and robotics colleagues elsewhere in Germany. ... Strauss and a handful of other insect biologists have turned to robotics experts. By programming simple robots to react to stimuli and move in particular ways, they can test biological hypotheses about which neural networks an insect uses to navigate. And the biologists hope to return the favour. The algorithms they use to direct their biorobots could in the future help design smarter and more agile robots, capable of overcoming many barriers without direction from humans." Hungry Robots. By Tony Belpaeme and Andreas Birk. ACM Crossroads Student Magazine, 8.2 (Winter 2001). "In this article, we first introduce three basic properties of behavior-based robots. Then we describe a prototype alife experiment with an ecosystem of different types of robots competing for energy. We also explain why we found diverse collections of robots more interesting to study than single robots." AI’s Half-Century. By Margaret A. Boden. AI Magazine 16(4): Winter 1995, 96-99. "Evolutionary robotics aims at a still closer biological parallel. Its hardware isn’t hand designed but automatically evolved. This approach uses 'genetic algorithms' (GAs), widely used in AI for problem solving of many kinds. GAs produce random mutations, or crossovers, in a program’s rules. The most useful of the resulting rules, given the task environment, are used (with high probability) for further 'breeding.' After many generations, the system may be highly efficient. For instance, the 'brains' of simple robots, and their sensorimotor anatomy, have been evolved in this way. This is an example of work in artificial life ('A-Life'). A-Life studies self-organizing, self-replicating, adaptive sys- tems and (more generally) the emergence of ordered complexity from simple rules. It’s closely related to AI. Indeed, because intelli- gence is a property of living systems, AI might be seen as a subarea of A-Life." Science, art, technology crux of art history class. By Monique Bos. The Chronicle (Savannah College of Art and Design; February 16, 2007). "The intersection of science and art via technology provides the starting point for a special topics course conceived and developed by Edward Shanken, Ph.D., an art history professor at the Savannah College of Art and Design. Shanken’s course, Cybernetics, Telematics and the Posthuman in Art and Culture, engages recent explorations of life, reality and interactivity by artists, scientists and those who cross between the disciplines. ... The focus of class Feb. 12 was on artificial life. Shanken began his lecture by responding to a student’s question about the distinction between artificial intelligence and Alife, as it’s often called. 'A.I. attempts to replicate human intelligence, whereas Alife attempts to emulate the behavior of organic life systems,' he explained. 'Alife may or may not be intelligent.' ... 'How is Alife living or not living?' he asked. 'How do we determine the quality and status of being?' ... He talked about the need to discover what’s at stake in this research and possible ramifications -- such as the formation of 'robots’ rights' groups." You make my heart beep. Scientists are experimenting with robots that will eventually be able to reproduce. By Dylan Evans. The Guardian (February 14, 2002). "The idea of allowing robots to evolve has given rise to a new but rapidly expanding field of research known as evolutionary robotics. Although it shares many of the insights of artificial life, which pioneered the use of genetic algorithms in the 1970s and 1980s, evolutionary robotics is distinguished by its insistence on making the leap from 2D computer-animations to 3D physically embodied machines." The emotional machine. "Steve Grand, designer of the artificial life program Creatures, talks about the stupidity of computers, the role of desire in intelligence and the coming revolution in what it means to be 'alive.'" By Suzy Hansen. Salon.com (January 2, 2002).
Non-Symbolic AI - Lecture 1. From Inman Harvey's Non-Symbolic Artifical Intelligence (2005) course, University of Sussex. "AI has tended to concentrate on logic, on calculation, on formal systems as the kind of intelligence to emulate in machines. But recently -- particularly with the new field of Artificial Life (Alife) -- people have widened their ideas of what counts as 'intelligence'. The ability of a bird to navigate between N. Europe and S. Africa is amazing, displays some kind of adaptive intelligence -- but does it use logic?" - Lecture Slide 18. Artificial Life meets Entertainment: Lifelike Autonomous Agents. By Pattie Maes of the MIT Media Lab. In: Clicking In, Hot Links to a Digital Culture, edited by Lynn Hershman Leeson, Bay Press, Seattle, 1996. "Artificial Life shares with Artificial Intelligence its interest in synthesizing adaptive autonomous agents. Autonomous agents are computational systems that inhabit some complex, dynamic environment, sense and act autonomously in this environment, and by doing so realize a set of goals or tasks that they are designed for." Living Machines - Technology and biology are converging fast. The result will transform everything from engineering to art - and redefine life as we know it. By Christopher Meyer, Jason Lohn, Karl Jacob, Dick Morley, Shana Ting Lipton, Marco Dorigo, Avery Pennarun. Wired Magazine (February 2004; Issue 12.02). "Copernicus demoted humanity by removing Earth from the center of the universe. Darwin showed that, rather than being made in God's image, people were merely products of nature's experimentation. Now, advances in fields as disparate as computer science and genetics are dealing our status another blow. Researchers are learning that markets and power grids have much in common with plants and animals. ... It turns out that many of life's properties - emergence, self-organization, reproduction, coevolution - show up in systems generally regarded as nonliving." Swarm Behavior - A single ant or bee isn't smart, but their colonies are. The study of swarm intelligence is providing insights that can help humans manage complex systems, from truck routing to military robots. By Peter Miller. National Geographic Magazine (July 2007). "'Ants aren't smart,' [Deborah M.] Gordon says. 'Ant colonies are.' A colony can solve problems unthinkable for individual ants, such as finding the shortest path to the best food source, allocating workers to different tasks, or defending a territory from neighbors. As individuals, ants might be tiny dummies, but as colonies they respond quickly and effectively to their environment. They do it with something called swarm intelligence. ... . It relies instead upon countless interactions between individual ants, each of which is following simple rules of thumb. Scientists describe such a system as self-organizing. ... If you're looking for a role model in a world of complexity, you could do worse than to imitate a bee." Swarm-Bots: Swarm of Mobile Robots able to Self-Assemble and Self-Organize. By Stefano Nolfi, Jean-Louis Denebourg, Dario Floreano, Luca Gambardella, Francesco Mondada and Marco Dorigo. (ERCIM News No. 53, April 2003). "Swarm-bots are a collection of mobile robots able to self-assemble and to self-organize in order to solve problems that cannot be solved by a single robot. These robots combine the power of swarm intelligence with the flexibility of self-reconfiguration as aggregate swarm-bots can dynamically change their structure to match environmental variations. SWARM-BOTS, a project funded by the Future and Emerging Technologies program of the European Community (project IST-2000-31010), focuses on the design and the implementation of self-organising and self-assembling biologically-inspired robots." Simulated evolution gets complex. By Kimberly Patch. Technology Research News (May 21/28, 2003). "It has taken more than five decades, but the electronic computer is now powerful enough to simulate evolution." Network builds itself from scratch. By Kimberly Patch. Technology Research News (March 26/April 2, 2003). "Drawing heavily on the chemistry of biology, researchers from Humboldt University in Germany have devised a way for electronic agents to efficiently assemble a network without having to rely on a central plan. The researchers modeled their idea on the methods of insects and other lifeforms whose communications lack central planning, but who manage to form networks when individuals secrete and respond to chemical trails. The researchers found that what works for ants and bacteria also works for autonomous pieces of computer code. ... Rather than determining the structure of a network in a top-down approach of hierarchical planning, agents found nodes and created connections in a bottom-up process of self-organization." Calculating Swarms - Ant teamwork suggests models for computing faster and organizing better. By Ivars Peterson. Science News, Vol. 158, No. 20 (November 11, 2000). "In effect, astonishing feats of teamwork emerge from a large number of unsupervised individuals following a few simple rules. This sort of self-organizing cooperative behavior among ants, bees, and other social insects has become the envy of engineers and computer scientists as they work to solve tough path-finding, scheduling, and control problems in industrial and other settings. In recent years, studies of ant behavior have suggested powerful computational methods for finding alternative traffic routes over congested telephone lines and novel algorithms for governing how robots operating independently would work together." Seeing Around Corners. By Jonathan Rauch. The Atlantic (April 2002). "The new science of artificial societies suggests that real ones are both more predictable and more surprising than we thought. Growing long-vanished civilizations and modern-day genocides on computers will probably never enable us to foresee the future in detail -- but we might learn to anticipate the kinds of events that lie ahead, and where to look for interventions that might work." Digital critters shed light on human sleep. By Michael Reilly. New Scientist (September 29, 2007; Issue 2623: page 28). "Digital 'organisms' that learn to sleep when energy is scarce and harvest it when it's abundant could help explain why sleep evolved in animals. The lifelike programs might also make gadgets more energy efficient. To simulate early life forms, Benjamin Beckman and colleagues at Michigan State University in East Lansing created 3600 self-replicating digital organisms each with its own refillable energy store and a 'genome' made of computer code to govern when the organism replenishes its store. Every time one of the organisms replicates, a portion of its energy store gets used up. To keep stores topped up, the organism executes a simple logic operation that uses up some energy, but results in it getting more back. ... Together with colleague Philip McKinley, Beckman is adapting the organisms to enable them to regulate energy consumption in wireless sensor networks."
Evolutionary Systems and Artificial Life. Lecture notes from Luis Rocha. "This course presents an overview of the field of Evolutionary Systems and its applied branch of Artificial Life. The historical and philosophical foundations of evolutionary thought are explored with particular emphasis on computational simulations of its models. Topics include: Self-Organizing Systems, Natural Selection, Dynamic Systems, Boolean Networks, Cellular Automata, Genetic ALgorithms, Evolutionary Robotics, etc." Terror Games - Can computer games be devised to model the thinking and predict the actions of allies, enemies and even terrorists? Some in the U.S. government think so. Are they playing God? By Jeffrey Rothfeder. Popular Science (February 2004). "Agent-based modeling is a child of complexity theory, which holds that the organization of complex systems hinges on the interplay of seemingly haphazard individual events. Complicated patterns -- how ants behave collectively, how terrorists choose targets -- emerge from what appears to be randomness. ... In 1984 the Santa Fe Institute (SFI) was formed to examine how the actions of individual animate or inanimate objects combine to influence and create complex systems. Among the groundbreaking research to come out of SFI was the work of Christopher Langton, known as the founder of the field of artificial life. Langton developed a simulation program called Swarm that was inspired by the collective behavior of social animals like bees and birds. Swarm has proven highly versatile; it's been used to model nuclear fission chain reactions, rain forest ecosystems, and investor's stock-picking strategies. Sims creator Will Wright was a frequent visitor to SFI in the early '90s when he was developing his first games, including SimAnt, which replicated the problem-solving activities in an ant colony."
Nature-Inspired Computing - Increased understanding of biological systems will lead to breakthroughs in computing and artificial intelligence. By Nigel Shadbolt. IEEE Intelligent Systems (January - February 2004). "It isn't hard to recognize the influence of biological processes and methods on our science and technologies. Norbert Wiener's cybernetics was very much influenced by feedback and control processes that he observed in biological systems. Warren McCulloch and Walter Pitts' characterization of the neuron owed much to their understanding of biology, mathematics, and electronics. In artificial intelligence and intelligent systems, we've also kept the faith with living systems even when not aiming to build exact simulations. AI and IS have been fundamentally interested in the phenomenology of living systems - perception, decision making, action, and learning. So we might say that we've been doing nature-inspired computing all along." Robot swarms 'evolve' effective communication. By Tom Simonite. NewScientist.com News (February 23, 2007). "Robots that artificially evolve ways to communicate with one another have been demonstrated by Swiss researchers [Dario Floreano, Sara Mitri, Stéphane Magnenat, and Laurent Keller]. The experiments suggest that simulated evolution could be a useful tool for those designing of swarms of robots. ... Cooperative communication evolved when selective success was judged at the group level – when many robots displayed efficient behaviour – or when the genomes of the robots were most similar – like biological relatives. ... 'These are significant findings for the biologically-inspired robotics community,' says Noel Sharkey, who is also evolving robot behaviour at Sheffield University, UK. Learning how to evolve robots instead of writing their behaviour from scratch could ultimately lead to more sophisticated behaviour, he says." The Artificial Life Roots of Artificial Intelligence. By Luc Steels (1994). Artificial Life Journal, Vol 1,1. MIT Press, Cambridge. Related Web SitesAlife and Art. From TPR/fusebox. Artificial Life at Indiana University. "Here are a few of the faculty involved in this discipline, with links to their home pages and projects." Artificial Life Laboratory at the Research Institute for Networks and Communications Engineering (RINCE) based in the School of Electronic Engineering at Dublin City University.
Autonomous NanoTechnology Swarm (ANTS) - Revolutionary Mission Architecture and AI Paradigm for Space Exploration. A Goddard Space Flight Center / Langley Research Center Partnership. "ANTS architecture, in keeping with the Biologically-inspired Engineering for Exploration Systems approach and inspired by an ant colony analogue is based on...." - from the Artificial Life as embodied in ANTS design and function page. "Avida is an auto-adaptive genetic system designed primarily for use as a platform in Digital or Artificial Life research. In lay terms, Avida is a digital world in which simple computer programs mutate and evolve. ... Avida is a joint project of the Digital Life Laboratory (headed by Chris Adami) at the California Institute of Technology and Richard Lenski's Microbial Evolution laboratory at Michigan State University." Boids (Flocks, Herds, and Schools: a Distributed Behavioral Model). Background and Update by Craig Reynolds. "The boids model is an example of an individual-based model, a class of simulation used to capture the global behavior of a large number of interacting autonomous agents. Individual-based models are being used in biology, ecology, economics and other fields of study."
CCSL - Cornell Computational Synthesis Lab. "At the Cornell Computational Synthesis Lab we explore biologically-inspired computational and physical processes that allow complex high-level systems to arise from low-level building blocks - automatically. We seek new biological concepts for engineering and new engineering insights into biology." CRESS - Centre for Research on Simulation in the Social Sciences. "There is growing interest in using computer simulation to explore issues in the social sciences. This site aims to provide resources for researchers in this emerging field. Simulation is a novel research method in most parts of the social sciences, including sociology, political science, economics, anthropology, geography, archaeology and linguistics. It can also be the inspiration for new, process-oriented theories of society. ... Experiments are not possible in most areas of social science. But with computer simulation, it becomes possible to build artificial societies of computational agents and carry out experiments under laboratory conditions, trying out different configurations and observing the consequences. Many computer games are, in effect, artificial societies, although they are of course constructed for entertainment rather than for analytical understanding. Some artificial life simulations are also mainly of interest because they are artificial societies." -from their Overview.
Devolab - The MSU Digital Evolution Laboratory: "The twin goals of the lab are to experimentally study digital organisms to improve our understanding of how natural evolution works, and then to apply this knowledge to solving computational problems." [See this news article above.] ECAL, the European Conference on Artificial Life.
The Flocking Robots Project at the Artificial Intelligence Laboratory, Department of Information Technology, University of Zurich. "Flocking adresses a variety of important topics in the field of multiagent simulation and collective robotics which include agent interaction, kin recognition, and finally the emergence of collective behavior." And their flocking applet is simply beautiful! The Golem Project (Genetically Organized Lifelike Electro Mechanics). "[W]e conducted a set of experiments in which simple electro-mechanical systems evolved from scratch to yield physical locomoting machines. Like biological lifeforms whose structure and function exploit the behaviors afforded by their own chemical and mechanical medium, our evolved creatures take advantage of the nature of their own medium - thermoplastic, motors, and artificial neurons. We thus achieve autonomy of design and construction using evolution in a limited universe physical simulation, coupled to off-the-shelf rapid manufacturing technology. This is the first time robots have been robotically designed and robotically fabricated."
International Society of Artificial Life (ISAL). "Currently based at Reed College, ISAL is a democratic, international, professional society dedicated to promoting scientific research and education relatingto artificial life, including sponsoring conferences, publishing scientific journals and newsletters, and maintaining web sites related to artificial life. Artificial Life (published by MIT Press) is the official journal of ISAL, and the biannual International Conference on Artificial Life is the official scientific gathering of the Society." - excerpt from the Mission statement. "SimWorld is a free artificial life simulation (based on the free SIMAGENT toolkit developed by Aaron Sloman), which provides functionality for running different interacting agents and objects in a simulated, continuous environment. ... SimWorld Teaching is a modified version of the research platform SimWorld. It can be used for Alife experiments as well as the study of various single and multi-agent control systems." From Matthias Scheutz, Artificial Intelligence and Robotics Laboratory, Department of Computer Science and Engineering, University of Notre Dame. "The Swarm Development Group (SDG), is a not-for-profit organization dedicated to advancing the state-of-the-art in multi agent based simulation through the continued advancement of the Swarm Simulation System and support of the Swarm user community." The Swarms Project - Scalable sWarms of Autonomous Robots and Mobile Sensors. "The SWARMS project brings together experts in artificial intelligence, control theory, robotics, systems engineering and biology with the goal of understanding swarming behaviors in nature and applications of biologically-inspired models of swarm behaviors to large networked groups of autonomous vehicles. Our main goal is to develop a framework and methodology for the analysis of swarming behavior in biology and the synthesis of bio-inspired swarming behavior for engineered systems." Several institutions are involved in this project: University of Pennsylvania;Yale; UniversityMassachusetts Institute of Technology;University of California, Berkeley;University of California, Santa Barbara;Army Research Office; and Army Institute of Collaborative Biotechnology. VLAB, the Artificial Life Virtual Lab at Monash University."Artificial Life (ALife) is a new area of theoretical research that uses simulations to understand how complex organisation and behaviour emerges in living systems.The increasing prominence of computers has led to a new way of looking at the world. This view sees nature as a form of computation. That is, we treat objects as simple computers, each obeying its own set of laws.This site provides simple demonstrations that illustrate various important ideas and processes." Zooland. Excellent, one-stop shopping for your Alife needs. Related AI Topics Pages
More ReadingsArtificial Life Bibliography of On-line Publications. Compiled by Ezequiel A. Di Paolo, School of Cognitive and Computing Sciences, University of Sussex. A Robot for the Masses. By Francisco Goldman. The New York Times Sunday Magazine (November 28, 2004). "Mark Tilden, a robotic physicist formerly of Los Alamos National Laboratory and NASA, invented Robosapien, or at least the prototype, in an intense three-week effort in 2001. Tilden, who is in his 40's, described it as 'the first real mass-marketed humanoid robot.' I was told that it would be commercially available the summer of 2004 for $99. ... In his booming, grandiloquent voice, Tilden began a highly scientific-sounding explanation of why Robosapien's price was so low -- something to do with his pioneering work in analog robotics, which uses simple electronics parts and imitates the natural physics of nature rather than computer-driven digital mechanics. ... Tilden, who invented BEAM robotics, earned a maverick reputation by taking another approach. BEAM, an acronym for 'biology, electronics, aesthetics and mechanics,' replaces digital processing with analog circuits. Tilden employed minimalist electronics -- even spare Walkman parts, pieces of old Atari processors -- to construct 'mechanical life forms' that interact with their environments. Rather than the ones and zeroes of digital processing, analog circuits produce continuous waves, allowing mechanisms to mimic the pendulum dynamic of animal movement." Philosophy of Artificial Life Bibliography. Composed by Brian Keeley at the Center for the Philosophy of Nature and Science Studies (CPNSS), University of Copenhagen. "Purpose: To gather together citations and minimal annotations of all work concerning philosophical issues in the pursuit of Artificial Life. This is to include work of 'professional' philosophers, scientific work with important discussions of foundational issues, as well as seminal & landmark work in the field itself." Programming the Post-Human: Computer science redefines "life." By Ellen Ullman. Harper's (2002)Vol. 305, No. 1829: 60-70. "Based on the same foundations as modern robotics - emergence theory - Alife's goal is the creation of software programs that exhibit the properties of being alive, what we call 'synthetic biology,' the idea that researchers can learn more about life 'in principle' if they free themselves of the specific conditions that gave rise to it on Earth." [p. 66] |
