Werner, G. M., & Dyer, M. G. (1991). Evolution of communication in artificial organisms. In Langton, C. G., Taylor, C., Farmer, J. D., & Rasmussen, S. (Eds.), Artificial Life II. AddisonWesley, Redwood City, CA.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....each agent has several conflicting objectives. In the proposed approach, separate communication programs are trained for each agent objective. Desigmng efficient and effective agent communication protocols for a large scale and complex multiagent system is difficult and timeconsuming. Werner [2] has proposed a multiagent system where the system evolves a simple communication protocol. In our previous research [6] we have proposed an approach applying genetic programming techniques, namely Automatically Defined Function Genetic Programming (ADF GP) to autonomously construct an ....

G.Werner and M. Dyer, "Evolution of Communication in Artificial Organisms ", Palificial Life II, Addisone-Wesley, 1991

....studied the effect of communication in providing action knowledge. For example, MacLennan [24] investigates the evolution of com munication in simulated worlds and concludes that the communication of local robot information can result in sig nificant performance improvements; Werner and Dyer [38] examine the evolution of communication which facilitates the breeding and propagation of artificial creatures; and Balch and Arkin [3] examine the importance of communi cation in robotic societies performing forage, consume, and graze tasks, finding that communication can significantly improve ....

Gregory M. Werner and Michael G. Dyer. Evolution of communication in artificial organisms. In Proceedings of the 2nd interdisciplinary workshop on synthesis and simulation of living systems, pages 659-687, 1991.

....introduces new challenges and thus the creation of new meanings. In the last five years, substantial progress has been reported on these objectives (see the overview in [13] There has been a first wave of research in the early 1990 s strongly inspired by artificial life concepts ( 6] [19], 3] 7] 17] This early research has often used a genetic approach and assumed that the set of meanings is fixed and given a priori by the designer. The primary emphasis was on understanding the emergence and evolution of animal communication rather than human natural language. There has ....

Werner, G. and M. Dyer (1991) Evolution of Communication in Artificial Organisms. In: Langton, C., et.al. (ed.) Artificial Life II. Addison-Wesley Pub. Co. Redwood City, Ca. p. 659-687. 22

....to the signal by approaching its source are under separate selective pressures. Males emitting the signal are more likely to have offspring than nonemitting males, and females that respond with the appropriate behavior are more likely to have offspring than nonresponding females. In fact Werner and Dyer (1991; 1994) have been able to evolve this type of language in a population of neural networks. But consider another scenario. An individual perceives the location of a mushroom but is unable to perceive the mushroom s detailed perceptual properties (e.g. its shape and color) because the mushroom is ....

Werner, G.M., & Dyer, M.G. (1991). Evolution of communication in artificial organisms. In C.G. Langton, C. Taylor, J.D. Farmer, & S. Rasmussen (eds.) Artificial Life II. Reading, Mass., Addison-Wesley.

....because ESP has been shown to be powerful in various control tasks [7, 8] we use ESP to evolve neural network controllers, rather than Genetic Programming to evolve program controllers. The role of communication in cooperative behavior has been studied in several Artificial Life experiments [26, 4]. These studies have shown that communication can be highly beneficial, allowing the communicating individuals to outperform the non communicating ones. However, most of these studies did not take into account the cost of communication such as the energy expenditure in signaling, or the danger ....

Werner, G. M., and Dyer, M. G. (1991). Evolution of communication in artificial organisms. In Langton, C. G., Taylor, C., Farmer, J. D., and Rasmussen, S., editors, Proceedings of the Workshop on Artificial Life (ALIFE '90), 659--687. Reading, MA: Addison-Wesley.

....other. The space inhabited by the two dimensional Turing machines described in [Rucker 1993] is a lattice on the surface of a torus. Even in the context of other applications rather than coupled computations, a number of systems have used well defined notions of space, such as in artificial life ([Werner and Dyer 1992]) neural netwoks ( Roska and Vandewall 1993] genetic algorithms ( Sannier II and Goodman 1987] and [Whitley 1993] and robotics. In contrast, although the activity in the Turing gas ( Fontana 1992] has been metaphorically described as taking place in a volume , this is in fact an abstract, ....

Gregory M. Werner and Michael G. Dyer. Evolution of communication in artificial organisms. In C. G. Langton, J. D. Farmer, S. Rasmussen, and C. Taylor, editors, Artificial Life: Proceedings of the second workshop on Artificial Life. Addison-Wesley, 1992.

.... Deneubourg, Theraulax Beckers 1992) Related work, including Assad Packard (1992) and Hogeweg Hesper (1985) demonstrated simulations of other simple organisms producing complex behaviors emerging from simple interactions, and the evolution of simple communication strategies in such systems (Werner Dyer 1990, MacLennan 1990) Until recently, work in Alife largely focused on systems with large numbers of extremely simple agents. In the last few years, several systems featuring multiple mobile robots have been used to implement and test Alife methodologies (Matari c 1992, Beckers, Holland Deneubourg ....

Werner, G. M. & Dyer, M. G. (1990), Evolution of Communication in Artificial Organisms, Technical Report UCLA--AI--90--06, University of California, Los Angeles.

....of the robot as opposed to being disembodied, with the input given by a human experimenter and the output again interpreted by the human observer. Some initial experiments have been reported in the Alife literature on how communication itself may arise to aid cooperation between agents [4] [13]. In this paper, we assume that there is already communication and focus instead on the grounding problem, as in [16] How the evolving language is anchored into the sensory and motor data streams generated through normal behavior. We also address the problem of the origin of meaning: How the ....

Werner, G. and M. Dyer (1991) Evolution of Communication in Artificial Organisms. In: Langton, C., et.al. (ed.) Artificial Life II. Addison-Wesley Pub. Co. Redwood City, Ca. p. 659-687.

....landscape. What are the prospects for such an automatic co evolutionary approach Initial work in this area is thin on the ground, but can be divided into two camps. Artificial, co evolutionary paradigms concerned with modelling natural phenomena such as communication include seminal work by Werner and Dyer (1991), in which male and female animats co evolved signal production and signal interpretation protocols in a simple animat world, allowing immobile females to attract blind males. Although research paradigms involving such idealised worlds are fraught with difficulties (Cliff Bullock, 3 1993) ....

Werner, G. M., & Dyer, M. G. (1991). Evolution of communication in artificial organisms. In Langotn, C. G., Taylor, C., Farmer, J. D., & Rasmussen, S. (Eds.), Artificial Life II - SFI Studies in the Sciences of Complexity, Vol. X, pp. 659 -- 687 Redwood City, California. Addison-Wesley.

....to the signal by approaching its source are under separate selective pressures. Males emitting the signal are more likely to have offspring than nonemitting males, and females that respond with the appropriate behavior are more likely to have offspring than nonresponding females. In fact Werner and Dyer (1991; 1994) have been able to evolve this type of language in a population of neural networks. But consider another scenario. An individual perceives the location of a mushroom but is unable to perceive the mushroom s detailed perceptual properties (e.g. its shape and color) because the mushroom is ....

Werner, G.M. & Dyer, M.G. (1991). Evolution of communication in artificial organisms. In C.G. Langton, C. Taylor, J.D. Farmer, & S. Rasmussen (eds.) Artificial Life II. Reading, Mass., Addison-Wesley.

....of communication may evolve under conditions of conflict and of co operation. Earlier models have often been constructed such that honest signalling 2 was always in the interests of both signallers and receivers. Thus, only co operative communication systems could possibly emerge. For example, Werner and Dyer (1991) postulated blind, mobile males and sighted, immobile females: the evolution of a signalling system was in the interests of both parties as it allowed mating to take place at better than chance frequencies. In MacLennan and Burghardt s (1994) model, signallers and receivers were rewarded if and ....

Werner, G. M., & Dyer, M. G. (1991). Evolution of communication in artificial organisms. In Langton, C. G., Taylor, C., Farmer, J. D., & Rasmussen, S. (Eds.), Artificial Life II. Addison-Wesley, Redwood City, CA.

....in the simulation of adaptive behaviour (SAB) and artificial life (AL) literature have often been constructed such that honest signalling is in the interests of both signallers and receivers any communication systems that evolve can therefore be described as cooperative. For example, Werner and Dyer (1991) postulated blind, mobile males and sighted, immobile females: the evolution of a signalling system was in the interests of both parties as it allowed mating to take place at better than chance frequencies. In MacLennan and Burghardt s (1994) model, signallers and receivers were rewarded if and ....

Werner, G. M., & Dyer, M. G. (1991). Evolution of communication in artificial organisms. In Langton, C. G., Taylor, C., Farmer, J. D., & Rasmussen, S. (Eds.), Artificial Life II. Addison-Wesley, Redwood City, CA.

....[10] Beer, Randall D. 59] Belew, Richard K. 60] Brown, C. T. 18] Cecconi, F. 47] Chou, Seng Cho Timothy, 52] Clark, Sean, 48] Collins, Robert James, 73, 74, 85, 86, 87] Cooper, Claus, 73, 74] Davidge, Robert, 61] Dewdney, A. K. 62] Donnart, Jean Yves, 11] Dyer, Michael G. [68, 69, 73, 74] Emmeche, Claus, 12, 29, 65] Flower, Joe, 49] Flowers, Margot, 73, 74] Forrest, Stephanie, 21, 34, 66] Furuya, T. 105] Gallagher, John C. 59] Garis, Hugo de, 26, 27, 106, 107, 108] Guillot, Agn es, 13, 19, 25] Heudin, J. C. 40] Horn, Jeffrey, 71] Hyvonen, Eero, 30, 41] ....

....Marlon, 101] Takashina, tomomi, 39] Taylor, Charles, 73, 74] Thearling, K. 23] Thompson, Adrian, 53] Thro, Ellen, 102] Todd, Peter M. 67, 98] Vaario, Jari, 24, 46, 103] Walnum, Clayton, 104] Wang, Alan, 73, 74] Watanabe, Shigeyoshi, 39] Wentworth, J. A. 38] Werner, Gregory M. [68, 69, 70] Wilson, Stewart W. 95, 96, 97, 98] Yokota, T. 28] total 92 articles by 87 different authors Subject index 13 4.7 Subject index All subject keywords of the papers given by the editor of this bibliography are shown next. The keywords neural networks , optimization , and evolution ....

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Gregory M. Werner and Michael G. Dyer. Evolution of communication in artificial organisms. In Langton et al. [56], pages 659--687. ga:GMWerner92a.

....4.4 Report series The following list contains references to all papers published as technical reports. The list is arranged in alphabetical order by the name of the institute. Advanced Telecommunications Research Institute International, 103] Santa Fe Institute, 66] University of California, [68, 73] total 4 reports in 3 institutes 4.5 Patents The following list contains the names of the patents of genetic algorithms in artificial life. The list is arranged in alphabetical order by the name of the patent. ffl none Patents 11 12 Genetic algorithms in artificial life 4.6 Authors The ....

....[10] Beer, Randall D. 59] Belew, Richard K. 60] Brown, C. T. 18] Cecconi, F. 47] Chou, Seng Cho Timothy, 52] Clark, Sean, 48] Collins, Robert James, 73, 74, 85, 86, 87] Cooper, Claus, 73, 74] Davidge, Robert, 61] Dewdney, A. K. 62] Donnart, Jean Yves, 11] Dyer, Michael G. [68, 69, 73, 74] Emmeche, Claus, 12, 29, 65] Flower, Joe, 49] Flowers, Margot, 73, 74] Forrest, Stephanie, 21, 34, 66] Furuya, T. 105] Gallagher, John C. 59] Garis, Hugo de, 26, 27, 106, 107, 108] Guillot, Agn es, 13, 19, 25] Heudin, J. C. 40] Horn, Jeffrey, 71] Hyvonen, Eero, 30, 41] ....

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Gregory M. Werner and Michael G. Dyer. Evolution of communication in artificial organisms. Technical Report UCLA-AI-90-06, University of California, Los Angeles, Computer Science Department, Artificial Intelligence Laboratory, Los Angeles, California 90024, November 1990. ga:GMWerner90.

.... Swiss Federal Institute of Technology Zurich, 137] Technische Universitat Munchen, 113] Technische Universitat Wien, 145] The Weismann Institute of Science, 63] Tulane University, 18] University of Alabama, 74, 125, 126, 127] University of Alberta, 263] University of California, [112, 164] University of Dortmund, 26, 153, 267] University of Illinois at Urbana Champaign, 120, 121] University of San Diego, 34, 35] University of Tennessee, 203] University of Virginia, 42] total 38 reports in 29 institutes 4.5 Patents The following list contains the names of the patents of ....

....Lawrence, 64, 65, 66] Deb, Kalyanmoy, 73, 74, 117, 123, 127] Decaestecker, Christine, 308] Denecker, M. 72] Deugo, Dwight, 75, 76] Diessel, O. F. 228] Dodd, Nigel, 78] Domingo, J. 13, 14] Dontas, Kejitan, 70] Dorigo, Marco, 79, 80] Durrani, T. S. 81] Dyer, Michael G. [112, 164] East, Ian, 204] Ebeling, Werner, 83] Eckardt, H. 147] Eggert, H. 85] Elia, Paul V. 139] Eshelman, Larry J. 264] Farmer, J. Doyne, 86] Feldberg, Rasmus, 246] Feldhousen, E. L. 51] Ferri, F. 13, 14] Flowers, Margot, 164] Fogarty, Terence C. 87, 88, 89, 90, 91] Fogel, ....

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Gregory M. Werner and Michael G. Dyer. Evolution of communication in artificial organisms. Technical Report UCLA-AI-90-06, University of California, Los Angeles, Computer Science Department, Artificial Intelligence Laboratory, Los Angeles, California 90024, November 1990. ga:GMWerner90.

....this paper is informed by the use of computational simulation techniques. A large body of computational modelling work has demonstrated that nonrandom genetic transmission (i.e. natural selection) of innate communication systems is capable of producing optimal, innate communication systems (e.g. Werner and Dyer (1991), Ackley and Littman (1994) MacLennan and Burghardt (1994) Levin (1995) Cangelosi and Parisi (1996) Oliphant (1996) Bullock (1997) de Bourcier and Wheeler (1997) Di Paolo (1997) Werner and Todd (1997) Noble (1998) A growing body of computational modelling work suggests that iterated ....

Werner, G. and M. Dyer (1991). Evolution of communication in artificial organisms. In C. Langton, C. Taylor, J. Farmer, and S. Rasmussen (Eds.), Artificial Life 2, pp. 659--687. Redwood City, CA: Addison-Wesley.

....Ding, A. M. G. 418] Ding, H. 164, 165] Distefano, G. 46] Dorey, Robert E. 457] Dorigo, Marco, 166, 167, 168, 169, 170, 171, 172, 463, 464] Dorndorf, Ulrich, 547] Driessche, Raf Van, 551] Drijkoningen, Guy, 613] Duckstein, J. 102] Dumont, Guy A. M. 411] Dyer, Michael G. [236, 354] Dymek, A. 173] Ebeling, Werner, 176] Eberhart, R. C. 177] Eiben, Agoston E. 178] Eisenhammer, Thomas, 641] Elias, John G. 179, 180, 181] El Keib, A. A. 164, 165] Ellis, C. 182] English, Thomas M. 183] Esbensen, Henrik, 184] Eshelman, Larry J. 617, 618, 697] Fagg, ....

....688] Wakami, N. 689] Walker, Scott, 648] Wandrey, Christian, 223] Wang, Alan, 354] Wang, P. 423, 424, 425, 426] Watanabe, K. 670] Wechsler, Harry, 75] Weeks, Arthur R. 346] Weeks, G. E. 116] Weigand, W. A. 125] Subject index 19 Wei, Gerhard, 237] Werner, Gregory M. [236] Weuster Botz, Dirk, 223] Whinston, Andrew B. 668] Whitaker, Kevin W. 375] Whitley, Darrell, 617, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699] Wienke, Dietrich, 448] Wiggins, Ralphe, 700] Williams, Donald E. 705] Williams, Jesse, 701] Wilson, Stewart W. 608, 609] ....

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Gregory M. Werner and Michael G. Dyer. Evolution of communication in artificial organisms. In Langton et al. [39], pages 659--687. ga:GMWerner92a.

....structured communication systems, which depend in part on the computational simulation of cultural and genetic processes fall into three main groups: 1. Those which suggest that genetic transmission between generations alone is capable of developing and refining innate communication systems (e.g. Werner and Dyer, 1991; Ackley and Littman, 1994; MacLennan and Burghardt, 1994; Levin, 1995; Cangelosi and Parisi, 1996; Oliphant, 1996; Bullock, 1997; de Bourcier and Wheeler, 1997; Di Paolo, 1997; Werner and Todd, 1997; Noble, 1998) 2. Those which suggest that cultural transmission between generations alone is ....

Werner, G. and M. Dyer (1991). Evolution of communication in artificial organisms. In C. Langton, C. Taylor, J. Farmer, and S. Rasmussen (Eds.), Artificial Life 2, pp. 659--687. Redwood City, CA: Addison-Wesley.

....communication, rather than the reward being assessed by the agents based on how communication helps them solve a task at hand. Our employing the nested mental models and the knowledge base approach further sets our work apart from Steels work, as well as from related research reported in [2, 30]. We think that initiation and enrichment of an agent communication language can be accomplished by the mechanism of negotiation, developed in the fields of economics and game theory [23, 24] and automated in recent work in artificial intelligence [15, 26, 27] Here, we are motivated by the ....

G. M. Werner and M. G. Dyer. Evolution of communication in artificial organisms. In C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors, Artificial Life II, SFI Studies in the Sciences of Complexity, pages 659--687. Addison-Wesley, 1991.

....from the final category the fitness of an individual must have the potential to be affected by the state of the environment or by others in the population. Much of the other work investigating the evolution of communication belongs to this category of models (MacLennan Burghardt, 1994; Werner Dyer, 1991; Bullock, 1997; Noble Cliff, 1996) as an external selection regime is being used to drive the evolutionary search process. However this does not alter the plausibility of the models, it only changes the potential dynamics of the search processes. Once again the nature of the hypothesis being ....

Werner, G. M., & Dyer, M. G. (1991). Evolution of communication in artificial organisms. In Langton, C. G., Taylor, C., Farmer, J. D., & Rasmussen, S. (Eds.), Artificial Life II. AddisonWesley, Redwood City, CA.

....neural network approach in order to address the problem of how to attach the meaning to a word, e.g. how can one agent s perception and description of the world make sense for another agent that is physically different. Examples of related work on agent communication and social behaviour are [12] [15], 14] 1] and [13] 17] Our 2 approach is different since it combines the following aspects. 1) The learning of the language is not implicit in the mechanisms and the learning architecture which we use. 2) Communication is not treated as a specialised module inside the control architecture ....

G. M. Werner and M. G. Dyer, (1992) `Evolution of communication in artificial organisms', Proc. of the Second Artificial Life Workshop, C. G. Langton, C. Taylor, J. D. Farmer and S. Rasmussen editors, pages 659-687.

.... work resulting from this interest has consistently failed to address issues of current interest within evolutionary biology, typically preferring to demonstrate the potential for communicative behavior to evolve under some selective pressure favoring information exchange (e.g. MacLennan, 1991; Werner Dyer, 1991). As a result this largely exploratory body of work has made little impact within the evolutionary biology literature. The time has come to demonstrate the worth of this modeling approach by producing research that interfaces with that published in biology journals and presented at biology ....

Werner, G. M., & Dyer, M. G. (1991). Evolution of Communication in Artificial Organisms. In Langton, C. G., Taylor, C., Farmer, J. D., & Rasmussen, S. (Eds.), Artificial Life II --- SFI Studies in the Sciences of Complexity, Vol. X, pp. 659--687 Redwood City, California. Addison-Wesley.

.... Similar approaches are currently under study in social sciences [7] 8] The multi agent paradigm seems well adapted to the study of these phenomena (see discussion in [6] Interesting results have already been obtained for different areas of language: simple communication codes [2] 13] 15] [22], coordination [4] 5] meaning and class formation [16] conventional lexicons [10] 17] 20] phonetics [3] and syntax [1] 9] 18] An overview of this approach is given in [19] This paper focuses on the links between class formation and lexicon building. This topic is a fundamental issue in ....

....[19] This paper focuses on the links between class formation and lexicon building. This topic is a fundamental issue in cognitive science, linguistics and philosophy (see [12] Most of the existing computational models study how agents can associate a single word with a referent [13] 15] 17] 21][22]. The referents can be categories, classes of objects, concepts either predefined in the model or evolving from processes distinct from the language formation itself. This amounts to assuming that an object table corresponds to a concept table independently of the agents naming it a table . ....

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G. M. Werner and M. G. Dyer. Evolution of communication in artificial organisms. In C. G. Langton, C. Taylor, and J. Farmer, editors, Artificial Life II, Vol.X of SFI Studies in the Sciences of Complexity, Redwood City, Ca., 1991. Addison-Wesley Pub.

....games those names that had the highest score. This generates the desired positive feedback loop bringing the group progressively towards global coherence. The naming game has been explored through computational simulations and is related to systems proposed and investigated by [MacLennan, 1991] [Werner and Dyer, 1991], and [Oliphant, 1996] We have developed more complex variations of the game where the meaning consist of symbolic descriptions derived from discrimination games [Steels, 1997a] The game has also been implemented on physically grounded mobile robotic agents [Steels and Vogt, 1997] and on ....

G. M. Werner and M. G. Dyer. Evolution of communication in artificial organisms. In C. G Langton, C. Taylor, and J.D. Farmer, editors, Artificial Life II, Vol.X of SFI Studies in the Sciences of Complexity, Redwood City, Ca., 1991. AddisonWesley Pub.

....the units in a connectionist net. Furthermore, the agents in many artificial life models are themselves controlled by internal connectionist nets (e.g. Todd Miller 1991; Ackley Littman 1992; Belew, McInerney, Schraudolph 1992; Cliff, Harvey, Husbands 1993; Parisi, Nolfi, Cecconi 1992; Werner Dyer 1992). In addition, for decades connectionism has explored recurrent architectures and unsupervised adaptive learning algorithms, both of which are echoed in a general manner in much artificial life modeling. But there are important differences between typical artificial life models and many of the ....

Werner, G. M., & Dyer, M. G. 1992. Evolution of communication in artificial organisms. In C. Langton, C. Taylor, D. Farmer, & S. Rasmussen (Eds.), Artificial life II. Reading, MA: Addison-Wesley.

....and its weight. For the first the signed character ( in the range [ 127,127] ae R) is recast as an unsigned integer (in the range [0,255]ae R) and its value modulus 20 (the number of units in the network) establishes the 8 many examples exist of successfully employed strong direct encoding. See [7] for an example. 9 see [2] 6] and [8] for some recent examples of incorporating structural details of the connectionist network on the genome. 10 see [8] for an example of such inclusive coding. 11 the name hybrid used is solely for the purpose of distinguishing between the two encoding ....

Werner, G.M., and Dyer, M.G. Evolution of communication in artificial organisms. In Farmer, J.D., Langton, C., Rasmussen, S.,and Taylor, C., editors, Artificial Life II. Reading, MA: Addison-Wesley,1991.

....related work also report on a variety of simulations of simple organisms producing complex behaviors emerging from simple interactions. Schmieder (1993) reports on an experiment in which the amount of knowledge agents have about each other is increased and decreased based on local encounters. Werner Dyer (1990) and MacLennan (1990) describe systems that evolve simple communication strategies. On the more theoretical end, Keshet (1993) describes a model of trail formation that fits biological data. Work in Artificial Life is related to the work in this thesis in that both are concerned with exploiting ....

Werner, G. M. & Dyer, M. G. (1990), Evolution of Communication in Artificial Organisms, Technical Report UCLA--AI--90--06, University of California, Los Angeles.

....is much closer to the process of natural selection than evolutionary computation models. Previous works on IPD and evolution like (Axelrod 1987 ; Fogel 1993 ; Lindgren and Nordal 1994) are artificial evolution models in the sense defined here. This also the case of artificial ecology models as (Werner and Dyer 1991). By choosing f i = 32 X j=1 q i IPD ij : we implicitly made the hypothesis of no spatial distribution of the population. With a finite population, it formulates as : Hypothesis NS. At each generation, every individual meets every other one once, its fitness is its average score over ....

Werner G. and Dyer M. : Evolution of communication in artificial organisms, in Artificial Life 2, Addison Wesley, pp. 659-687, 1991.

....by simple captors) to scalar outputs. The link weights are tuned by a gradientinspired optimization method. Still more interesting, considering our own goals, is the emergence of a dialog between Steels robots (Steels 1996) A pseudo dialog in a simulated world (a grid) is described also in (Werner Dyer 1992); here, a genetic algorithm is used to tune a similar collection of connection weights. These models, despite their behavioral properties, are hardly extensible, and show little flexibility. They don t seem enough relevant from a cognitive science point of view, as they aren t backed by an ....

Werner, G., and Dyer, M. 1992. Evolution of Communication in Artificial Organisms. In Langton, C. G. et al. eds.

.... input to a one digit output, and evolve under suitable conditions to establish cooperation through message exchange (MacLennan 1992) Crumpton 1994) Similarly, language driven mating in a simulated grid environment leads to one or several coherent dialects expressing spatial directives (Werner Dyer 1992). On the other side, Hashimoto Ikegami 1997) focused their experiment on syntax, using symbolic agents without any environment or semantics. Real world robots require much more complex control structures for perception and action. Steels has convincingly shown how a lexicon denoting real world ....

Werner G. & Dyer M. 1992, Evolution of Communication in Artificial Organisms, Artificial Life II, Santa Fe, New Mexico, pp. 659-687.

....will automatically select against poor actions. Recently there has been much interest in evolving neural networks with genetic algorithms (Belew et al. 1990; Jefferson et al. 1991; Kitano 1990; Koza and Rice 1991; Moriarty and Miikkulainen 1994b; Schaffer et al. 1992; Whitley et al. 1990; Werner and Dyer 1991). In most applications, the population consists of complete neural networks and each network is evaluated independently of other networks in the population. During evolution, the population converges towards a single dominant network. Such convergence is desirable if it occurs at the global ....

Werner, G. M., and Dyer, M. G. (1991). Evolution of communication in artificial organisms. In Farmer, J. D., Langton, C., Rasmussen, S., and Taylor, C., editors, Artificial Life II. Reading, MA: Addison-Wesley.

....explained by the fact that natural selection provides a very effective means of tuning innate systems of communication. Game theoretic approaches (Warneryd, 1993; Blume, Kim, and Sobel, 1993; Kim and Sobel, 1995; Skyrms, 1996) and an increasingly large literature of computational modeling work (Werner and Dyer, 1991; Oliphant, 1993; Oliphant, 1996; MacLennan and Burghardt, 1994; Ackley and Littman, 1994; Levin, 1995; Cangelosi and Parisi, 1996; Bullock, 1997; Werner and Todd, 1997; de Bourcier and Wheeler, 1997; Di Paolo, 1997; Noble, 1998) have given us a good understanding of how such innate mappings can ....

Werner, G. and M. Dyer (1991). Evolution of communication in artificial organisms. In C. Langton, C. Taylor, J. Farmer, and S. Rasmussen (Eds.), Artificial life II, pp.

....small robots conducting a search and retrieve task using either an infra red or incandescent recruitment signal. The authors reported an approximately 50 improvement in performance for target acquisition using this type of signal. The work as reported in [1] is very preliminary. Werner and Dyer [52] have studied the evolution of communication in synthetic agents. They have demonstrated that directional mating signals can evolve in these systems given the presence of societal necessity. MacLennan [38] also has studied this problem and has concluded that communication can evolve in a society ....

Werner, G. and Dyer, M., 1990. Evolution of Communication in Artificial Organisms. Technical Report UCLA-AI-90-06, AI Laboratory, University of California, Los Angeles.

....elements of a finite discrete set. Since we are creating an artificial world, there is no need to equip it with familiar environmental 3 Our experiment may be contrasted with that of Werner and Dyer, who also observed the evolution of communication, but in a more complicated synthetic world. [31] That such different experimental designs resulted in qualitatively similar observations is evidence that synthetic ethology can reveal general properties of communication. Figure 1: Topology of the Environment features such as temperature, water supply, food supply, etc. We can define the laws ....

Werner, Gregory M, and Michael G. Dyer. "Evolution of Communication in Artificial Organisms." Artificial Life II, Santa Fe Institute Studies in the Sciences of Complexity, edited by Doyne Farmer, Christopher Langton, Steen Rasmussen, and Chuck Taylor, proceedings vol. XII. Redwood City, CA: Addison-Wesley, 1991.

....within a single, rich environment (Steels, 1994; McFarland, 1994) although at this stage in the research the agents are still designed. Others have approached the problem of communication bottom up, turning towards adaptation and evolution as a source of insight (Yanco and Stein, 1993; Werner and Dyer, 1992; Robbins, 1994; MacLennan, 1992; MacLennan and Burghardt, 1993; Collins and Jefferson, 1991, 1992; de Bourcier and Wheeler, 1994) but their work all shares an emphasis on discrete communication. Yanco and Stein (1993) investigate a follow the leader task in which one agent, the leader, ....

....Pollack The Evolution of Communication symbols to represent the command, broadcasts the symbol to the other agents, and the subordinates respond. A reinforcement algorithm governs both the encodings of the leader and responses of the subordinates; over time, a consensus emerges between the two. Werner and Dyer (1992) describe a more complex environment in which simulated animals must communicate to find mates. Females, while stationary, can sense potential mates within a limited range and call out to them by emitting a signal. Males, wandering around the environment, lack the capacity to produce signals or ....

Werner, G. M. and Dyer, M. G. (1992). Evolution of communication in artificial organisms. In Langton, C. G., Taylor, C., Farmer, J. D., and Rasmussen, S., editors, Artificial Life II, pages 659-687. Addison-Wesley.

....have studied the effect of communication in providing action knowledge. For example, MacLennan [24] investigates the evolution of communication in simulated worlds and concludes that the communication of local robot information can result in significant performance improvements; Werner and Dyer [38] examine the evolution of communication which facilitates the breeding and propagation of artificial creatures; and Balch and Arkin [3] examine the importance of communication in robotic societies performing forage, consume, and graze tasks, finding that communication can significantly improve ....

Gregory M. Werner and Michael G. Dyer. Evolution of communication in artificial organisms. In Proceedings of the 2nd interdisciplinary workshop on synthesis and simulation of living systems, pages 659--687, 1991.

.... more complexity in living systems, beginning with the origin of life itself, 5] and of artificial life experiments seeking to synthesise a spontaneous increase in complexity [4] Of particular interest here are related experiments on the origin of communication [6] the origin of vocabulary [15] [12] and the growth in complexity of syntax [3] There is also a secondary motivation. Understanding the mechanisms by which a language self organises, may make a bottom up approach to artificial intelligence possible [10] Although much progress has been made recently on the synthesis and ....

Werner, G. and M. Dyer (1991) Evolution of Communication in Artificial Organisms. In: Langton, C., et.al. (ed.) Artificial Life II. Addison-Wesley Pub. Co. Redwood City, Ca. p. 659-687.

....life models of communication Artificial life (AL) models of the evolution of communication are often constructed such that honest signalling is in the interests of both signallers and receivers any communication systems that evolve can therefore be described as cooperative. For example, Werner Dyer (1991) postulated blind, mobile males and sighted, immobile females: the evolution of a signalling system was in the interests of both parties as it allowed mating to take place at better than chance frequencies. In MacLennan Burghardt s (1994) model, signallers and receivers were rewarded if and only ....

Werner, G. M., and Dyer, M. G. 1991. Evolution of communication in artificial organisms. In Langton, C. G.; Taylor, C.; Farmer, J. D.; and Rasmussen, S., eds., Artificial Life II. Addison-Wesley, Redwood City, CA.

....language can be learned, why language keeps evolving, and why there are so many diverse languages. The artificial life approach has already shed some light on these issues. Several researchers have carried out experiments to investigate the origin of communication [5] the origin of vocabulary [6], and the growth in complexity of syntax [3] These researchers assume that genetic evolution is the main driving force towards new structure, coherence, and more complexity. But humans learn the languages present in their environment during their life time. There is no evidence that a particular ....

Werner, G. and M. Dyer (1991) Evolution of Communication in Artificial Organisms. In: Langton, C., et.al. (ed.) Artificial Life II. Addison-Wesley Pub. Co. Redwood City, Ca. p. 659-687.

....communication during their lifetime. In this sense the work differs from most approaches based on genetic algorithms. ffl There is no direct feedback to agents about the success of their communication; only feedback about their behavior excluding communication is available, as is advocated in [Werner and Dyer, 1991]. Thus, a coherent system of communication can only come about if agents use the signals they perceived to choose their actions and at the same time use the feedback on their behavior to adapt their lexicon. Several authors describe the development of communication where agents are either teacher ....

Werner, G. M. and Dyer, M. G. (1991). Evolution of communication in artificial organisms. In Langton, C. G., Taylor, C., Farmer, J., and Rasmussen, S., editors, Artificial Life II, SFI Studies in the Sciences of Complexity, volume X. Addison-Wesley.

....1982) it seems less likely that parasite selection pressure could directly foster the signal diversity within populations or across generations that is our main interest here. Much closer to our current concerns is (perhaps not surprisingly) an earlier simulation created by the first author: Werner and Dyer s (1992) evolution of signals generated by females to guide blind males towards them for mating. The communication in this case functioned to allow reproduction between the roving males and the stationary, signalling females they succeeded in finding; thus we can say that this communication evolved via ....

.... this form of sexual selection, we can see the beginnings of signal diversity in this simulation: signal dialects appeared in some runs, leading Werner and Dyer to speculate that these communication protocols could provide a natural way of establishing genetic barriers that spontaneously emerge (Werner Dyer, 1992, p. 685) and lead to distinct coexisting species. But these spontaneous breeding barriers emerge only slowly in the rather diffuse sexual selection operating in this model; in the simulations we report here, we greatly increase the power of sexual selection by allowing individuals to sample ....

Werner, G.M., and Dyer, M.G. (1992). Evolution of Communication in Artificial Organisms. In C. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen (Eds.), Artificial Life II (pp. 659-687). Reading, MA: AddisonWesley.

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Werner, G. M., & Dyer, M. G. (1991). Evolution of communication in artificial organisms. In Langton, C. G., Taylor, C., Farmer, J. D., & Rasmussen, S. (Eds.), Artificial Life II. AddisonWesley, Redwood City, CA.

No context found.

G. M. Werner and M. G. Dyer. Evolution of communication in artificial organisms. In C. Langton, C. Taylor, J. Farmer, and S. Rasmussen, editors, Artificial Life II, pages 659--687. Addison-Wesley, 1991. 27

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Gregory M. Werner and Michael G. Dyer, "Evolution of Communication in Artificial Organisms," in Artificial Life II, volume X, edited by C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen (AddisonWesley, Redwood City, CA, 1991).

No context found.

Werner, Gregory M. and Dyer, Michael G. (1991). Evolution of communication in artificial organisms. In Langton, Christopher G., Taylor, Charles, Farmer, J. Doyne, and Rasmussen, Steen (editors). Artificial Life II, SFI Studies in the Sciences of Complexity. Volume X. Redwood City, CA: Addison-Wesley. Pages 659687.

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Werner, G. and M. Dyer (1991) Evolution of Communication in Artificial Organisms. In: Langton, C., et.al. (ed.) Artificial Life II. Addison-Wesley Pub. Co. Redwood City, Ca. p. 659-687.

No context found.

G. M. Werner and M. G. Dyer. Evolution of communication in artificial organisms. In C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, editors, Artificial Life II: SFI Studies in the Sciences of Complexity, Volume X, pages 511--547, 1991.

No context found.

Werner, G. M., and Dyer, M. G. Evolution of communication in artificial organisms. In Langton, C. G., Taylor, C., Farmer, J. D., and Rasmussen, S., editors, Artificial Life II, pp. 659--687. Reading, MA: Addison-Wesley, 1991. 6

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Werner, G. and M. Dyer (1991) Evolution of Communication in Artificial Organisms. In: Langton, C., et.al. (ed.) Artificial Life II. Addison-Wesley Pub. Co. Redwood City, Ca. p. 659-687.

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Werner, Gregory M. and Dyer, Michael G.: Evolution of Communication in Artificial Organisms in Artificial Life II Addison-Wesley Publishing Co,, 1992.

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