Christopher G. Langton, Charles Taylor, J. Doyne Farmer, and Steen Rasmussen (eds.), Artificial life 2, Addison-Wesely, 1992, Santa Fe Institute Studies in the Sciences of Complexity. Vol. 10.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....evaluation function. considered to be difficult to construct, and most of the systems proposed so far were based on rigid application knowledge with a small amout of adaptivity, controlled by the user models which are also rigid. However, recent research in machine learning and artificial life[14] suggests that various techniques can be applied to make interface systems learn or evolve to fit to each user s needs. For example, Maes proposes learning interface agents [13] 15] which gradually learn to assist the individual user by observing the user s actions, getting user feedback, and ....

Langton, C. G., Taylor, C., Farmer, J. D., and Rasmussen, S., Eds. Artificial Life II, vol. X of Santa Fe Institute Studies in the Sciences of Complexity. AddisonWesley, 1991.

....still fit only to the phenomenon of life seems to become a way of reassuring ourselves of our uniqueness. Consequently, ploughing this field is left to philosophy and the theory of sciences. In recent years, the term artificial life has become widely used (for developments in that field see [26]) generally without too much concern about precise definitions Artificial organisms are logical automata which exhibit life like processes [25] on the other hand, research in the field of the origin of life and of the mechanisms of evolution concentrated on the phenomena of living ....

C. E. Langton. Artificial Life. Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. VI. Addison Wesley (Redwood City), 1989.

....left to philosophy and the theory of sciences. In recent years, the term artificial life has become widely used (for developments in that field see [26] generally without too much concern about precise definitions Artificial organisms are logical automata which exhibit life like processes [25]; on the other hand, research in the field of the origin of life and of the mechanisms of evolution concentrated on the phenomena of living organisms. 1.3 Pattern and structure The examples for physical systems exhibiting life like behavior given above lead to the question of the nature of the ....

R. Laing. Artificial Life, chapter Artificial Organisms: History, Problems, Directions, pages 49--61. Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. VI. Addison Wesley (Redwood City), 1989.

....That is to say, our networks tend to be chaotic but only weakly so. They lie at the transition between ordered and chaotic behavior, sometimes called the edge of chaos . It has been conjectured that complex emergent systems (biological and otherwise) evolve toward such a phase transition (Langton et al. 1992). Our results can be interpreted to suggest that evolution is not essential, but that such behavior is inherent in the system itself as its complexity increases. Our networks automatically exhibit both unpredictability (sensitivity to initial conditions) and long term memory (small Lyapunov ....

Langton, C.G., Taylor, C., Farmer, J.D., Rassmussen, S. (Eds.), 1992. Arti"cial Life II, Santa Fe Institute Studies in the Sciences of Complexity, vol. 10, Addison-Wesley, Redwood City, CA.

.... attempt to elucidate certain aspects of reproduction in well defined mathematical frameworks, such as the cellular automata [5, 6, 7] spinglas models [8, 9] or nonlinear dynamical systems [10, 11, 12, 13] More recently, complex models have been introduced under the heading of artificial life [14, 15, 16]. In this letter we shall introduce another simple system, some members of which show the characteristics of self replication. It is based on the re interpretation of logical and mathematical operations and was inspired by findings made nearly a decade ago in biochemistry. Kruger et al. 17] and ....

Langton, C.G., (ed.), Artificial Life, Santa Fe Institute Studies on the Sciences of Complexity, Proc. Vol. VI, Addison-Wesley, Reading, MA, 1989

....the Emergent Design Group (EDG, 1] at M.I.T. is to research architectural morphology with a specific focus on the emergent and adaptive properties of architectural form. One avenue we pursue is the development of interactive software tools based on the principles of artificial life (ALife, e.g. [2, 3]) and evolutionary algorithms (EAs, e.g. 4] Another avenue is the development of prototype building systems. We seek to apply both technologies to real world problems. Through the development of our EA based and ALife based tools we seek to generate, discover, simulate, analyze, display, and ....

C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors. Artificial Life II. Santa Fe Institute Studies in the Sciences of Complexity. Addison-Wesley, Reading, MA, 1992.

....the Emergent Design Group (EDG, 1] at M.I.T. is to research architectural morphology with a specific focus on the emergent and adaptive properties of architectural form. One avenue we pursue is the development of interactive software tools based on the principles of artificial life (ALife, e.g. [2, 3]) and evolutionary algorithms (EAs, e.g. 4] Another avenue is the development of prototype building systems. We seek to apply both technologies to real world problems. Through the development of our EA based and ALife based tools we seek to generate, discover, simulate, analyze, display, and ....

C. G. Langton, editor. Artificial Life. Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. VI. Addison-Wesley, Reading, MA, 1989.

....satisfied, they are bonded again, as shown in Fig. 4. Such reaction processes in Atomoid show how its features differ from other artificial models. First, the reaction 0.968071 0.419281 A 0.478281 5.714773 0.351692 2.859282 B 0.654436 0.132388 0.512205 4.269322 0.939977 3.282287 C 0. 378829 4.983282 0.288201 1.678595 0.356823 0.806595 0.703298 2.633307 D r (k ) Fig. 6 Atoms in simulation. A B C D Fig. 7 Component ratio of atoms. activation energy population 5000 threshold for absorbing photons E f = 0.7 = 6 Table 1 Parameters of simulation. dynamics are ....

....step 0.0 0.2 0.4 0.6 0.8 1.0 1.2 0 200 400 600 800 1000 without photon with disordered photons with ordered photons Fig. 8 Activation degree of system. step 0.0 0.4 0.8 1.2 1.6 2.0 0 200 400 600 800 1000 without photon with disordered photons with ordered photons Fig. 9 Internal energy of atoms. Fig. 8 indicates the activation degree of the system when the photon energy poured into the system is controlled in different ways. The degree is measured by the ratio of actual atomic reactions to all calculations. A lower activation degree means that few reactions have ....

[Article contains additional citation context not shown here]

Langton, C. G., ed.: Artificial Life, Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. VI, pp. 1-47, Addison-Wesley, 1989.

....and adaptation: A computer can t evolve or adapt on its own; it is restricted to change only in ways speci ed ahead of time by its programmer. Although these arguments are still believed by a great many people, all of them have been disproven in one way or another in the eld of Arti cial Life [1, 3, 19, 20, 21, 22, 23]. In this paper I will focus on those issues most closely related to Darwinism self reproduction and evolution. 2 Self Reproduction in Computers The self reproduction argument above is the most mathematical one: it states that reproduction in a computer would lead to an in nite regress. ....

C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors. Articial Life II. Santa Fe Institute Studies in the Sciences of Complexity. Addison-Wesley, Reading, MA, 1992.

....23:110, 1986. #80# R. Rosen. Life Itself: A Comprehensive Inquiry into the Nature, Origin, and Fabrication of Life. Columbia University Press, New York, 1991. #81# D. Sangiorgi. Expressing Mobility in Process Algebras: First Order and Higher Order Paradigms. PhD dissertation, University of Edinburgh, 1992. 58 #54# Y. Lafont. From proof nets to interaction nets. In J. Y. Girard, Y. Lafont, and L. Regnier, editors, Advances in Linear Logic, London Mathematical Society Lecture Note Series, pages 225#247, Cambridge, 1995. Cambridge University Press. #55# R. Lalement. Computation as Logic. Prentice ....

In C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors, Arti#cial Life II, Santa Fe Institute Studies in the Sciences of Complexity, pages 93#141, Redwood City, 1992. Addison-Wesley.

....of simple local rules followed by the agents. In other words, the agents have a limited horizon and limited prevision and computation capabilities but, in spite of these limitations, the system as a whole appears to behave according to regular patterns. Artificial Life is a new discipline [1] that strives to use computers, robots, and other artificial means to the study of life like phenomena. The approach is synthetic rather than analytic and it works mainly by putting together systems that behave, in some respects, like living organisms. Computer simulation of populations of ....

Langton C. G.(Ed.): Artificial Life. Santa Fe Institute Studies in the Sciences of Complexity. Addison-Wesley, 1989.

....is satisfied, they are bonded again, as shown in Fig. 4. Such reaction processes in Atomoid show how its features differ from other artificial models. First, the reaction 0.968071 0.419281 A 0.478281 5.714773 0.351692 2.859282 B 0.654436 0.132388 0.512205 4.269322 0.939977 3.282287 C 0. 378829 4.983282 0.288201 1.678595 0.356823 0.806595 0.703298 2.633307 D q r (k ) Fig. 6 Atoms in simulation. A B C D Fig. 7 Component ratio of atoms. activation energy population 5000 threshold for absorbing photons DE f = 0.7 y = p 6 Table 1 Parameters of simulation. dynamics are completely ....

....of detailed simulation. step 0.0 0.2 0.4 0.6 0.8 1.0 1.2 0 200 400 600 800 1000 without photon with disordered photons with ordered photons Fig. 8 Activation degree of system. step 0.0 0.4 0.8 1.2 1.6 2.0 0 200 400 600 800 1000 without photon with disordered photons with ordered photons Fig. 9 Internal energy of atoms. Fig. 8 indicates the activation degree of the system when the photon energy poured into the system is controlled in different ways. The degree is measured by the ratio of actual atomic reactions to all calculations. A lower activation degree means that few reactions have ....

[Article contains additional citation context not shown here]

Langton, C. G., ed.: Artificial Life, Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. VI, pp. 1-47, Addison-Wesley, 1989.

....alternatives to the single carbon based paradigm for life found on earth. One such alternative involves computational structures (such as programs within the digital environment of a computer) that exploit computer time to organize memory in order to survive, reproduce, and improve themselves (Langton 1989; Langton et al. 1991; Langton 1991a, 1991b) This exploitative and organizational process operates within the constraints of the rules of interaction governing the milieu of computational structures. In this analogy, computer time corresponds to energy available from the environment and computer ....

Langton, Christopher G. (editor). Artificial Life, Santa Fe Institute Studies in the Sciences of Complexity. Volume VI. Redwood City, CA: Addison-Wesley. 1989.

....which at one time would have seemed a contradiction in terms. Approaches on these lines have been the subject of much recent interest, and conferences on similar themes have been held under the title of Artificial Life in Santa Fe in 1987, 1990 and 1992 (Langton 1989, Langton et al. 1991, Langton 1993) in Europe in 1991 and 1993 (Varela and Bourgine 1992, Goss 1993) with the titles Evolution, Games and Learning and Emergent Computation by the Center for Nonlinear Studies, Los Alamos, in 1985 and 1989 (Farmer et al. 1985, Forrest 1989) Simulation of Adaptive Behavior Conferences have ....

C. Langton, editor. Artificial Life III. Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. XVI, Addison Wesley., 1993.

....Life Cambridge, MA: MIT Press, 1991. is to search a fitness landscape for high values (where fitness can be either explicitly or implicitly defined) and GAs have been demonstrated to be efficient and powerful search techniques for a range of such problems (e.g. there are several examples in [19]) However, the details of how the GA goes about searching a given landscape are not well understood. Consequently, there is little general understanding of what makes a problem hard or easy for a GA, and in particular, of the effects of various landscape features on the GA s performance. In this ....

C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors. Artificial Life II. Santa Fe Institute Studies in the Sciences of Complexity. AddisonWesley, Reading, MA, 1992.

.... is not achieved in the conventional tightly coupled, centrally controlled way, but, instead, indirectly by the interaction of relatively primitive components with the world and among themselves [Steels 1991] Emergent functionality is one of the main themes of research in artificial life [Langton 1989]. In this paper, we use the genetic programming paradigm to evolve a computer program that exhibits emergent behavior and enables an autonomous mobile robot to follow the walls of an irregularly shaped room. The evolutionary process is driven only by the fitness of the programs in solving the ....

Langton, Christopher G. Artificial Life, Santa Fe Institute Studies in the Sciences of Complexity. Volume VI. Redwood City, CA: Addison-Wesley. 1989.

....interest for the evolution of computer programs. The area develops into two different directions: One is the study of artificial ecologies, where computer programs compete for access to resources inside the computer, like CPU time or memory space. This area has also been dubbed Artificial Life [1, 2] and leads to rich emergent phenomena, like parasitism, symbiosis, arms races between different software species. The other direction is the study of systems which evolve according to user defined behavior. This area is generally known as genetic or evolutionary programming [3, 4] In the latter ....

Langton, C.G., (ed.), Artificial Life, Santa Fe Institute Studies on the Sciences of Complexity, Proc. Vol. VI, Addison-Wesley, Reading, MA, 1989

....many systems in which the actions of simple, locallyinteracting components give rise to coordinated global information processing. Insect colonies, economic systems, the immune system, and the brain have all been cited as examples of systems in which emergent computation occurs (e.g. see [5, 11]) In the following, emergent computation refers to the appearance in a system s temporal behavior of information processing capabilities that are neither explicitly represented in the system s elementary components or their couplings nor in the system s initial and boundary conditions. Our ....

C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors. Artificial Life II. Santa Fe Institute Studies in the Sciences of Complexity. Addison-Wesley, Reading, MA, 1992.

....produce complex behaviors from interactions of simpler behaviors, the goal of developing models to predict behavior seems increasingly remote. Some researchers claim that behavior is in principle unpredictable, so the only way to design systems is as Nature does, by mutation and selection (e.g. [14], p. 25) A related argument is that AI systems are too complex to be modelled in their entirety. But, in fact, complex AAAI 90 Survey: Pulling Together or Pulling Apart Paul R. Cohen 21 systems can be modelled and behavior can be predicted if not accurately, at least accurately enough to ....

Langton, C. Artificial Life. Santa Fe Institute Studies in the Sciences of Complexity. 1989.

....activity is not simply on events in space time but the processes and Emergent Design seeks to formulate principles of architecture in this space of processes allowing space and time (Architecture) as we know it to emerge only at a secondary level. There are numerous concepts in the field of ALife (Langton 1989; Langton et al. 1992) that are advantageously applicable to an Architecture design process which emphasizes system level and constituent understanding. In ALife every component of a system, including elements of the environment, is conceptualized as being capable of agency. Thus, a component of ....

C. G. Langton, editor. Artificial Life. Santa Fe Institute Studies in the Sciences of Complexity, Proc. Vol. VI. Addison-Wesley, Reading, MA, 1989.

....simply on events in space time but the processes and Emergent Design seeks to formulate principles of architecture in this space of processes allowing space and time (Architecture) as we know it to emerge only at a secondary level. There are numerous concepts in the field of ALife (Langton 1989; Langton et al. 1992), that are advantageously applicable to an Architecture design process which emphasizes system level and constituent understanding. In ALife every component of a system, including elements of the environment, is conceptualized as being capable of agency. Thus, a component of the system may or may ....

C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors. Artificial Life II. Santa Fe Institute Studies in the Sciences of Complexity. Addison-Wesley, Reading, MA, 1992.

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C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors. Artificial Life II. Santa Fe Institute Studies in the Sciences of Complexity. Addison-Wesley, Reading, MA, 1992.

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