Saunders, G. M., & Pollack, J. B. (1996). The evolution of communication schemes over continuous channels. In Maes, P., Mataric, M., Meyer, J.-A., Pollack, J., & Wilson, S. W. (Eds.), From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, pp. 580--589. MIT Press / Bradford Books, Cambridge, MA.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....(Z. H. Zhou) for prey and predator avoidance in a virtual environment called BioLand. Kerce [7] created virtual marine snails controlled by artificial neural networks trained by Hebbian rule, which lived in a virtual ecosystem where food, sunshine, and turbulence existed. Saunders and Pollack [12] utilized recurrent neural networks to realize virtual ants that evolved a communication scheme over continuous channels which conveyed task specific information when the virtual ants were learning to follow broken trails of food. Cangelosi and Parsi [2] realized a virtual environment where a ....

Saunders G. M. and Pollack J. B. "The evolution of communication schemes over continuous channels." In: Proceedings of the 4th International Conference on Simulation of Adaptive Behavior. North Falmouth, MA, 1996, pp.580-589.

....II. EVOLUTION OF COMMUNICATION USING SIGNALS Evolutionary computation has recently been applied to studying the emergence and auto organisation of communication lexicons. Some models have been used for the simulation of the emergence of simple lexicons in populations of simulated organisms (e.g. [23], 4] 19] in small communities of robots [27] or in on line Internet agents [26] In these studies, organisms evolve shared lexicons for describing entities and relations of the environment. These models, that focus on lexicon emergence, do not make any explicit and direct reference to the ....

Saunders, G.M., & Pollack, J.B. (1996). The evolution of communication schemes over continuous channelx Proceedings of the SAB'96 Conference on the Simulation of Adaptive Behavior. Cambridge, MA: MIT Presx

....through the principle of self organization. A set of agents create their own vocabulary in a random manner, yet self organization occurs because the agents are coupled in the sense that they must conform to a common vocabulary in order to cooperate through communication. Saunders and Pollack [17] allow agents to communicate real valued signals through continuous communication channels. The signals decay over distance and an agent s input 3 on a channel reflects the summation of all the other agents signals along that channel. Saunders and Pollack assigned these agents to a task in which ....

Gregory M. Saunders and Jordan B. Pollack. The evolution of communication schemes over continuous channels. In P. Maes, M. Mataric, J.A. Meyer, and J.B. Pollack, editors, From Animals to Animats 4: Proceedings of the 4th International Conference on Simulation of Adaptive Behavior. MIT Press, 1996.

....for evolution a finding that could be related to the high level of diversity among human languages and to the similarities between sexual and cultural selection mechanisms. Some simulations use neural networks to model organisms and genetic algorithms to model evolution. For example, Saunders and Pollack (1996) have used recurrent neural networks and the GNARL (Saunders, Angeline, Pollack, 1994) evolutionary algorithm to study the evolution of continuous communicative systems, that is, the exchange of real valued signals in different input and output channels. The interaction protocol involves small ....

Saunders, G.M., & Pollack, J.B. (1996). The evolution of communication schemes over continuous channels. Proceedings of the SAB'96 Conference on the Simulation of Adaptice Behavior. Cambridge, MA: MIT Press.

....dominance interactions, spatial dynamics and emergent reciprocity in a virtual world. Another related work is that of Noble (NOBL98) who describes intention movements and the evolution of signaling in animal contests. Other varieties of communication have been studied in the SAB context (NOBL96, SAUN96) In particular, Reznikova and Ryabko apply Information Theory to the study of communication in ants and demonstrate that, in the communication system of these insects, the frequency of use of a message correlates with its length. The authors also demonstrate that the numerical competence of ants ....

G. M. Saunders and J. B. Pollack. The Evolution of Communication Schemes over Continuous Channels. In [SAB96].

....symbols. The model is analyzed according to the issues of the symbol grounding and symbol acquisition problems. 1. Introduction Computational models using genetic algorithms, neural networks, and robotics, have been used for studying the evolution of language and communication [13] Some models [2,10] have used neural networks and genetic algorithms for simulating the emergence of single word languages. For example, organisms controlled by neural networks evolve a shared lexicon of two signals for naming two different types of food sources [2] In other studies [4,12] agents use ....

Saunders, G.M., & Pollack, J.B. (1996). The evolution of communication schemes over continuous channels. Proceedings of the SAB'96 Conference on the Simulation of Adaptive Behavior. Cambridge, MA: MIT Press.

....Learning a Language We now however ask all agents to learn to communicate with each other: at this stage the whole population of agents exists in a shared environment and must learn to find a common language to describe this environment. We use a language comprising floating point numbers (as in [10]) rather than a discrete alphabet of terms since it is more easily extensible than a discrete representation would be. Each agent has a (perhaps different) representation of the environment. It also has the means to express to the others in the community its view of the environment. Its ....

G. M. Saunders and J. B. Pollack. The evolution of communication schemes over continuous channesl. In From Animals to Animats 4 - Proceedings of the Fourth International Conference on Adaptive Behaviour, 1996.

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Saunders, G. M., & Pollack, J. B. (1996). The evolution of communication schemes over continuous channels. In Maes, P., Mataric, M., Meyer, J.-A., Pollack, J., & Wilson, S. W. (Eds.), From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, pp. 580--589. MIT Press / Bradford Books, Cambridge, MA.

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