C. Langton et al., editors. Artificial Life II. Addison-Wesley, 1992.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....limit the kind of segmentation strategies which can realistically be implemented with current ANNs. In this paper we present a new approach to cardiac image segmentation which can overcome the aforementioned drawbacks. It is based on the idea, bor rowed from the field of Artificial Life [4], of selecting artificial creatures by means of genetic algorithms on the basis of their fitness to the surrounding environment [5, 6, 7] Our creatures, we call them Gnets (Genetic Networks) are basically a kind of re current ANNs which lives inside the image to be segmented (the ....

C. Langton, C. Taylor, J. D. Farmer, and S. Ras- mussen, eds., Artificial Life II. Reading, Massachusetts: Addison-Wesley, 1992.

....of plan. The performance of the reactive planning evolved by GA is much better for every environment. Environment Ordinary plan (from [18] Reactive plan 1 14,400 800 2 18,000 2,000 3 220,800 18,400 4. Artificial ant The problem of artificial ant used in our experiment is Santa Fe trail [19]. This problem is frequently referred to and used as a standard problem for comparing various learning techniques. The goal of Santa Fe trail problem is to train the ant to eat all food contained in the square 32 x 32 grid with a limitation amount of time (400 actions in our experiment) An ant ....

Langton, C. et al ed. 1991. Artificial Life II, Addison Wesley.

....and every researcher sees the field from her own perspective. C.G. Langton provides several approaches to a definition: In [62] his definition remains short: The study of man made systems that exhibit behaviors characteristic of natural living systems. He extends this definition in [63] to a futuristic outlook: Artificial Life is a field of study devoted to understanding life by attempting to abstract the fundamental dynamical principles underlying biological phenomena, and recreating these dynamics in other physical media such as computers making them accessible to ....

C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen. "Artificial life ii," 1992. 71

....most of us still agree with Jeremy. Where we find disagreement is on the answer to the spider s question. Artificial life must ask this question: With what do we compare artificial life The founding characterizations of artificial life comparing life as it could be with life as we knowit [29,30], or implementation independent computer life with space time energydependent material life [20] was a creative beginning, but this highly formal view of life was immediately questioned. Such abstract characterizations do not clearly separate science fiction and computer games from physical ....

.... of boundary conditions or constraints can self organize from deterministic dynamical laws, and what types can only emerge from a statistical bias on a heritable population distribution (i.e. natural selection) is a central problem in evolution theory and an active study in artificial life [30]. As with all such problems, the issue depends on the existence of an epistemic cut. 3.3 Measurement Defines an Epistemic Cut Like it or not, the epistemic cut in physical theory falls in Planck s unfathomable gull between dynamical and statistical laws. The possible trajectories of the world ....

Langton, C., Taylor, C., Farmer, J., and Rasmussen, S., eds., Artificial Life II, Addison-Wesley, Redwood City, CA.

....The wider scientific field of self organizing systems in nature is outside the present mandate. Our focus also is on deliberate engineering design to exploit useful self organizing effects, as distinct from the scientific understanding only, of selforganizing phenomena. Readers are referred to [2] to access the wider scientific field of artificial life. Self organizing neural networks are discussed in [3] and self organizational effects at the edge of chaos in [4] In telecommunications specifically, the only other area we are aware of where selforganizational tactics are being pursued is ....

C. Langton, Ed., Artificial Life II. Reading, MA: AddisonWesley, 1992.

.... robots will have to operate sooner or later The Artificial Life reminded opportunely in the early 90s that the ability of an agent to exhibit adaptive behaviors comes from the fact that it is physically situated in a dynamical environment, to which it adapts itself (rather than the contrary) [19, 22] . It is time now to apply this idea to the domain of social interactions as well as physical ones. Nobody would try to design service robots in an everyday environment, and still naively assume that a major component of this environment man, in fact would easily accept to adapt himself to ....

C. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, eds. Artificial Life II, London, 1990. Addison-Wesley.

....is no absolute security as trusted systems can cheat. But the process is completely open and robust as trust is not predefined, but it emerges from subtle interactions between the systems. The basic ideas of this process go back to two roots, namely the field of Artificial Life or short Alife [Ste94a, Lea90, Lan89] and the field of Evolutionary Game Theory [Smi84, Axe84, AH81, SP73] Before the process of the formation of trust can be described, it is necessary to first define the notion of trust itself as it is used here. The basis for trust is an intrinsic property of each individuum in form of the ....

Christopher G. Langton and et al. Artificial Life II. Addison-Wesley, Reading, MA, 1990.

....is to find a method to model intelligence as adaptive behavior, rather than simulate real robots. We include development process and plasticity (learning) as individual adaptation, and natural sexual selection and genetic changes as evolutionary adaptation. This work is related to Artificial Life [3, 4, 5] as well as to Simulated Adaptive Behavior [6] where biological systems have been used as a source of inspiration. These approaches are a response to an argument that AI has failed to model intelligent behaviors, but modelled only intelligent solutions instead. The Genetic Algorithms are often ....

C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, eds., Artificial Life II. Addison-Wesley Publishing Company, 1992.

....It is almost as if we were stuck in the middle ages when our only experience of light was that it came from fire. It is difficult to understand any complex phenomenon when you cannot abstract the concept from its implementation. This is the raison d etre for the field of Artificial Life. [13, 15, 14, 3, 23] In the long view, researchers in Artificial Life seek to simulate and even synthesize life in novel media in order to understand the phenomenon of life itself. Only then can we hope to separate the historical accidents that led to life on Earth from the systematic constraints that shaped it. ....

C. G. Langton, C. E. Taylor, J. D. Farmer, and S. Rasmussen, editors. Artificial Life II, Reading, MA, 1992. Addison-Wesley.

....seriously limit the kind of segmentation strategies which can realistically be implemented with current ANNs. In this paper we present a new approach to cardiac image segmentation which can overcome the aforementioned drawbacks. It is based on the idea, borrowed from the field of Artificial Life [4], of selecting artificial creatures by means of genetic algorithms on the basis of their fitness to the surrounding environment [5, 6, 7] Our creatures, we call them Gnets (Genetic Networks) are basically a kind of recurrent ANNs which lives inside the image to be segmented (the environment) ....

C. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, eds., Artificial Life II. Reading, Massachusetts: Addison-Wesley, 1992.

....and arguably modern computers. One source of difficulty arises from nonlinear interactions among system components. Nonlinearities can lead to unanticipated emergent behaviors, a phenomenon that has been well documented and studied in physical, chemical, biological, and social systems (e.g. see [7, 29]) as well as in some forms of computation [13] Nonlinear systems with interesting emergent behavior are often referred to as complex systems. A second form of complexity arises when the primitive components of the system can change their specification, or evolve, over time. Systems with this ....

Langton, C. G., Taylor, C., Farmer, J. D., & Rasmussen, S. (Eds.). (1992). Artificial life II. Redwood City, CA: Addison-Wesley.

....in naturally occurring systems are independent of one s position in the system. One of the primary motivations for studying CA has therefore been to improve our understanding of complex natural systems. Since von Neumann, CA have been used to model many complex physical and biological processes [27, 24, 26]. They have been used to investigate issues surrounding the origins of life [23, 24, 26] and to design a reliable parallel computer [8] In a more speculative vein, it has been suggested that quantum fields may actually be cellular automata [31] and that future computers may be large crystals of ....

....the primary motivations for studying CA has therefore been to improve our understanding of complex natural systems. Since von Neumann, CA have been used to model many complex physical and biological processes [27, 24, 26] They have been used to investigate issues surrounding the origins of life [23, 24, 26] and to design a reliable parallel computer [8] In a more speculative vein, it has been suggested that quantum fields may actually be cellular automata [31] and that future computers may be large crystals of smart molecules grown artificially, each crystal operating like a cellular automaton [7] ....

C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors. Artificial Life II. Addison-Wesley Publishing Co., 1992.

....develop, with the modeller prejudicing the developmental possibilities as little as possible. Something along these lines has already been implemented to a certain extent in the sugarscape model of Axtell and Epstein (1995) paralleling the artificial worlds movement in the biology domain (cf. Langton 1989 and Langton, Taylor, Farmer and Rasmussen 1992). While this direction of research has generated much excitement, it has not avoided the fate of many overhyped scientific trends in the form of a sceptical backlash (see Horgan 1995) Be that as it may, in the following we will limit ourselves to those models rooted in the economics tradition ....

Langton, C.G., Taylor, C.,Farmer, J. D.and Rasmussen, S. (eds), 1992, Artificial Life II, Redwood City, CA: Addison-Wesley.

....and robotics . try to understand life by attempting to abstract the fundamental dynamical principles underlying biological phenomena, and recreating these dynamics in other physical media such as computers making them accessible to new kinds of experimental manipulation and testing. LAN 91, p. xiv] Autonomous Agent research tries to overcome some fundamental problems of traditional symbolic AI, which we can only mention in the scope of this article, that is the symbol grounding problem [HAR 90] the frame problem [PYL 87] the frame of reference problem [CLA 89] and the ....

Langton, C., Taylor, C., Farmer, J. D. & Rasmunssen, S. (1991). Artificial Life II. Addisson-Wesley, New Jersey, 1991.

....1) fully interconnected ANN and 2) the modularized ANN. In addition, the same functions were sorted according to four different measures in the literature dealing with Boolean functions, namely, the already discussed GSM structural type (range 1 6) 3] and in addition the Lambda count (range 0 4) [4], Fluency (range 1 9) theory developed in [15] original idea by Ashby [13] and Boolean Length (range 1 10) this is the minimum number of Boolean operations necessary to represent the binary string (related to Kolmogorov complexity) 15] Values of these four complexity measures for the 88 ....

Langton C.G., Taylor C. , Farmer J.D. & S. Rasmussen (eds.), Artificial Life II, Addison-Wesley, 1992.

....in artificial life. Abstract accounts of artificial life like the foregoing have only limited value. A better taste of the real flavor of artificial life research can be had by reviewing typical ALife models such as those found in recent conference proceedings (Farmer et al. 1986, Langton 1989b, Langton et al. 1991). 2 Fourteen Questions The field of artificial life raises a wide variety of philosophical questions. More importantly, an appreciation of artificial life might provide the wherewithal to find their answers. The following list, although not exhaustive, should convey the diversity of issues ....

Langton, C. G., C. E. Taylor, J. D. Farmer, and S. Rasmussen, eds. 1991. Artificial Life II. SFI Studies in the Sciences of Complexity, Vol. X. Redwood City, CA: Addison-Wesley.

....Wilson 1995) In (Wilson 1995) Wilson adapted Hancock and Kittler s Bayesian framework (Hancock and Kittler 1990a) to derive a probabilistic measure of the quality of a match, which was optimised by gradient ascent. Cross has investigated several global optimisation approaches to this problem in (Cross 1998), including simulated annealing and genetic search. The practical applications of graph matching are myriad, but include object recognition (Dickinson et al. 1992) feature based stereo correspondence (Horaud and Skordas 1989) image registration (Wilson 1995) and medical imaging (Dumay et al. ....

.... study of biological genetics to evolutionary optimisation, for example, Muhlenbein in (Muhlenbein 1994; Muhlenbein and Schlierkamp Voosen 1995) and Bedau in (Bedau 1995) Recently, Cross has given an accurate theoretical account of the search properties of the genetic algorithm for inexact matching (Cross 1998). While general theoretical models are beneficial in understanding the processes at play in genetic algorithms, their use in practical settings is limited. Any deviation from the assumptions made in the model could invalidate it, and the model may not be particularly informative as to what the ....

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In C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen (Eds.), Artificial Life II. Addison-Wesley. M. Jelasity and J. Dombi (1998). GAS, a concept on modeling species in genetic algorithms.

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C. Langton et al., editors. Artificial Life II. Addison-Wesley, 1992.

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Langton, C., Taylor C., Farmer, J. D. & Rasmussen, S. (eds.), 1991, Artificial Life II, Santa Fe Inst. Studies in the Sciences of Complexity, Reading, Massachusetts: Addison-Wesley. 12

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

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Langton, C., C. Taylor, J. D. Farmer & S. Rasmussen (eds.) (1991), Artificial Life II, Addison-Wesley, Redwood City, CA.

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Langton C.G., Taylor C. , Farmer J.D. & S. Rasmussen (eds.), Artificial Life II, Addison-Wesley, 1992.

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Langton, C. Taylor, J. D. Farmer, & S. Rasmussen (Eds.), Artificial Life II (pp. 295-312). Reading, MA: Addison Wesley. Packard, N. H. (1989). Intrinsic adaptation in a simple model for evolution. In C.

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C.G. Langton, C. Taylor, J.D. Farmer, and S. Rasmussen, editors. Artificial Life II. Addison Wesley, 1991.

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Langton, C. L., Farmer, J. D., Rasmussen, S., & Taylor, C. (Eds.). (1992). Artificial Life II.

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