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Abstract

This dissertation identifies the conditions necessary to establish a system of communication in a population of individuals, whether through evolution or learning. A definition of communication is proposed that encompasses the behavior of species ranging from flowers to human beings, and a formal framework for modeling such behavior is presented. Through the use of computational simulations, it is shown that systems of communication evolve in cases where such behavior conveys a selective advantage to both sender and receiver. It is also demonstrated that factors such as kin selection and reciprocal altruism can result in the establishment of communication even when there is no direct pressure on the transmission of signals. In the case of learned communication, it is argued that observational learning is the appropriate learning model. Learning strategies that simply imitate the behavior of others, however, are not suitable. Instead, a learning mechanism must optimize its behavior so as best to communicate with the population it is observing. A Bayesian learning procedure designed to maximize the probability of communicative success is shown to be capable not only of learning an existing communication system, but also constructing such a system from random initial signaling behavior. To examine how animals might actually implement such a procedure, network learning models are considered. It is shown that a simple form of Hebbian learning, well within the grasp of most animals, has the required properties. Given this, it is surprising that learned systems of communication are not more frequent. Evidence from the animal social learning literature suggests that the primary reason for this may be that observational learning is difficult, if not impossible, for non-human animals. Given this, he most basic explanation for why only humans have language may not lie in the ability of learn a complex, syntactic form of communication, but rather in the ability to learn any system of communication at all.

@phdthesis{oliphant97formalApproaches,
  author={M. Oliphant},
  title={Formal Approaches to Innate and Learned Communication: Laying the Foundation for Language},
  year={1997},
  school={Department of Cognitive Science, University of California, San Diego},
  url={http://www.isrl.uiuc.edu/~amag/langev/paper/oliphant97formalApproaches.html}
}

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