Multi-Agent Simulation of Emergence of Schwa Deletion Pattern in Hindi

Recently, there has been a revival of interest in multi-agent simulation techniques for exploring the nature of language change. However, a lack of appropriate validation of simulation experiments against real language data often calls into question the general applicability of these methods in modeling realistic language change. We try to address this issue here by making an attempt to model the phenomenon of schwa deletion in Hindi through a multi-agent simulation framework. The pattern of Hindi schwa deletion and its diachronic nature are well studied, not only out of general linguistic inquiry, but also to facilitate Hindi grapheme-to-phoneme conversion, which is a preprocessing step to text-to-speech synthesis. We show that under certain conditions, the schwa deletion pattern observed in modern Hindi emerges in the system from an initial state of no deletion. The simulation framework described in this work can be extended to model other phonological changes as well.Language Change, Linguistic Agent, Language Game, Multi-Agent Simulation, Schwa Deletion

Simple models of distributed co-ordination

Distributed co-ordination is the result of dynamical processes enabling independent agents to coordinate their actions without the need of a central co-ordinator. In the past few years, several computational models have illustrated the role played by such dynamics for self-organizing communication systems. In particular, it has been shown that agents could bootstrap shared convention systems based on simple local adaptation rules. Such models have played a pivotal role for our understanding of emergent language processes. However, only few formal or theoretical results have been published about such systems. Deliberately simple computational models are discussed in this paper in order to make progress in understanding the underlying dynamics responsible for distributed coordination and the scaling laws of such systems. In particular, the paper focuses on explaining the convergence speed of those models, a largely under-investigated issue. Conjectures obtained through empirical and qualitative studies of these simple models are compared with results of more complex simulations and discussed in relation to theoretical models formalized using Markov chains, game theory and Polya processes

Cooperation, social selection, and language change: an experimental investigation of language divergence

In this thesis, I use an experimental model to investigate the role of social pressures in stimulating language divergence. Research into the evolution of cooperation has emphasised the usefulness of ingroup markers for swiftly identifying outsiders, who pose a threat to cooperative networks. Mechanisms for avoiding cheats and freeriders, which tend to rely on reputation, or on (explicit and implicit) contracts between individuals, are considerably less effective against short-term visitors. Outsiders, moreover, may behave according to different social norms, which may adversely affect cooperative interactions with them. There are many sources of markers by which insiders and outsiders can be distinguished, but language is a particularly impressive one. If human beings exploit linguistic variation for this purpose, we might expect the exploitation to have an influence on the cultural evolution of language, and to be involved in language divergence, since it introduces a selective pressure, by which linguistic variants are selected on the basis of their social significance. However, there is also a neutral, mechanistic model of dialect formation that relies on unconscious accommodation between interlocutors, coupled with variation in the frequency of interaction, to account for divergence. In studies of real-world communities, these factors are difficult to tease apart. The model described in this thesis put real speakers in the artificial environment of a computer game. A game consisted of a series of rounds in which players were paired up with each other in a pseudo-random order. During a round, pairs of players exchanged typed messages in a highly restricted artificial "alien language". Each player began the game with a certain number of points, distributed between various resources, and the purpose of sending messages was to negotiate to exchange these resources. Any points given away were worth double to the receiver, so, by exchanging resources, players could accumulate points for their team. However, the pairings were anonymous: until the end of a round, players were not told who they had been paired with. This basic paradigm allowed the investigation of the major factors influencing language divergence, as well as the small-scale individual strategies that contribute to it. Two major factors were manipulated: frequency of interaction and competitiveness. In one condition, all players in a game were working together; in another condition, players were put into teams, such that giving away resources to teammates was advantageous, but giving them to opponents was not. This put a pressure on players to use variation in the alien language to mark identity. A combination of this pressure and a minimum level of interaction between teammates was found to be sufficient for the alien language to diverge into "dialects". Neither factor was sufficient on its own. The results of these experiments suggest that a pressure for the socially based selection of linguistic variants can lead to divergence in a very short time, given sufficient levels of interaction between members of a group