Language Evolution and Computation Bibliography

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Seth Bullock
2015
ECAL, pages 349-356, 2015
Iterated learning takes place when the input into a particular individual’s learning process is itself the output of another individual’s learning process. This is an important feature to capture when investigating human language change, or the dynamics of culturally learned ...MORE ⇓
Iterated learning takes place when the input into a particular individual’s learning process is itself the output of another individual’s learning process. This is an important feature to capture when investigating human language change, or the dynamics of culturally learned behaviours in general. Over the last fifteen years, the Iterated Learning Model (ILM) has been used to shed light on how the population-level characteristics of learned communication arise. However, until now each iteration of the model has tended to feature a single immature language user learning from their interactions with a single mature language user. Here, the ILM is extended to include a population of immature and mature language users. We demonstrate that the structure and make-up of this population influences the dynamics of language change that occur over generational time. In particular, we show that, by increasing the number of trainers from which an agent learns, the agent in question learns a fully compositional language at a much faster rate, and with less training data. It is also shown that, so long as the number of mature agents is large enough, this finding holds even if a learner’s trainers include other agents that do not yet posses full linguistic competence.
2002
Adaptive Factors in the Evolution of Signaling SystemsPDF
Simulating the Evolution of Language 3.0:53-78, 2002
Х вн г и ди жз в и з гг к дджг йб в а в й л и в н иг из йв ей ийж зИ зй з ж йжз к знви мИ гж а ж а жв а м гвК Я джгдгз иг и л ж к лИ з в йб в а в й з гв бгв б вн в б а гббйв и гв знзи бзИ в г йз в гв и з а и к дж ззйж з Ћ иЙ в и гж в в б ви в в г зй знзи бзК Ь дгзз а ин и и йб в ...MORE ⇓
Х вн г и ди жз в и з гг к дджг йб в а в й л и в н иг из йв ей ийж зИ зй з ж йжз к знви мИ гж а ж а жв а м гвК Я джгдгз иг и л ж к лИ з в йб в а в й з гв бгв б вн в б а гббйв и гв знзи бзИ в г йз в гв и з а и к дж ззйж з Ћ иЙ в и гж в в б ви в в г зй знзи бзК Ь дгзз а ин и и йб в а в й ...
Artificial Life 8(1):97-100, 2002
Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and ...MORE ⇓
Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions. The major theme that emerged during these sessions was the identity and status of artificial life as a scientific endeavor.
1997
An Exploration of Signalling Behaviour by both Analytic and Simulation Means for both Discrete and Continuous ModelsPDF
ECAL97, 1997
Abstract Kurd's (1995) model of a discrete actionresponse game, in which the interests of signallers and receivers conflict, is extended to address games in which, as well as signal cost varying with signaller quality, the value of an observer's response to a signal is also ...