536 research outputs found
Modeling the emergence of a new language: Naming Game with hybridization
In recent times, the research field of language dynamics has focused on the
investigation of language evolution, dividing the work in three evolutive
steps, according to the level of complexity: lexicon, categories and grammar.
The Naming Game is a simple model capable of accounting for the emergence of a
lexicon, intended as the set of words through which objects are named. We
introduce a stochastic modification of the Naming Game model with the aim of
characterizing the emergence of a new language as the result of the interaction
of agents. We fix the initial phase by splitting the population in two sets
speaking either language A or B. Whenever the result of the interaction of two
individuals results in an agent able to speak both A and B, we introduce a
finite probability that this state turns into a new idiom C, so to mimic a sort
of hybridization process. We study the system in the space of parameters
defining the interaction, and show that the proposed model displays a rich
variety of behaviours, despite the simple mean field topology of interactions.Comment: 12 pages, 10 figures, presented at IWSOS 2013 Palma de Mallorca, the
final publication will be available at LNCS http://www.springer.com/lnc
Conventions spreading in open-ended systems
We introduce a simple open-ended model that describes the emergence of a
shared vocabulary. The ordering transition toward consensus is generated only
by an agreement mechanism. This interaction defines a finite and small number
of states, despite each individual having the ability to invent an unlimited
number of new words. The existence of a phase transition is studied by
analyzing the convergence times, the cognitive efforts of the agents and the
scaling behavior in memory and timeComment: 11 pages, 5 figure
Sharp transition towards shared vocabularies in multi-agent systems
What processes can explain how very large populations are able to converge on
the use of a particular word or grammatical construction without global
coordination? Answering this question helps to understand why new language
constructs usually propagate along an S-shaped curve with a rather sudden
transition towards global agreement. It also helps to analyze and design new
technologies that support or orchestrate self-organizing communication systems,
such as recent social tagging systems for the web. The article introduces and
studies a microscopic model of communicating autonomous agents performing
language games without any central control. We show that the system undergoes a
disorder/order transition, going trough a sharp symmetry breaking process to
reach a shared set of conventions. Before the transition, the system builds up
non-trivial scale-invariant correlations, for instance in the distribution of
competing synonyms, which display a Zipf-like law. These correlations make the
system ready for the transition towards shared conventions, which, observed on
the time-scale of collective behaviors, becomes sharper and sharper with system
size. This surprising result not only explains why human language can scale up
to very large populations but also suggests ways to optimize artificial
semiotic dynamics.Comment: 12 pages, 4 figure
How Do You Like Me in This: User Embodiment Preferences for Companion Agents
We investigate the relationship between the embodiment of an artificial companion and user perception and interaction with it. In a Wizard of Oz study, 42 users interacted with one of two embodiments: a physical robot or a virtual agent on a screen through a role-play of secretarial tasks in an office, with the companion providing essential assistance. Findings showed that participants in both condition groups when given the choice would prefer to interact with the robot companion, mainly for its greater physical or social presence. Subjects also found the robot less annoying and talked to it more naturally. However, this preference for the robotic embodiment is not reflected in the users’ actual rating of the companion or their interaction with it. We reflect on this contradiction and conclude that in a task-based context a user focuses much more on a companion’s behaviour than its embodiment. This underlines the feasibility of our efforts in creating companions that migrate between embodiments while maintaining a consistent identity from the user’s point of view
Emergence of communication in embodied agents evolved for the ability to solve a collective navigation problem
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Self-organizing communication in language games
From the point of view of semiotic dynamics language is an evolving complex dynamical system. In this perspective, unrevealing the mechanisms that allow for the birth of shared conventions is a major issue. Here we describe a very simple model in which agents negotiate conventions and reach a global agreement without any intervention from the outside. In particular we focus on the possibility of predicting on which of the several competing conventions the agreement is reached. We find from simulations that early created conventions are favored in the competition process and this advantage can be quantified. Beyond the specific results presented here, we think that this paper provides an example of a new way of investigating language features where simple models allow for the investigation of precise problems and, possibly, for analytical approaches
THSim v3.2: The Talking Heads simulation tool
The field of language evolution and computation may benefit from using efficient and robust simulation tools that are based on widely exploited principles within the field. The tool presented in this paper is one that could fulfil such needs. The paper presents an overview of the tool -- THSim v3.2 -- and discusses some research questions that can be investigated with it
Nonequilibrium dynamics of language games on complex networks
The naming game is a model of nonequilibrium dynamics for the self-organized emergence of a linguistic convention or a communication system in a population of agents with pairwise local interactions. We present an extensive study of its dynamics on complex networks, that can be considered as the most natural topological embedding for agents involved in language games and opinion dynamics. Except for some community structured networks on which metastable phases can be observed, agents playing the naming game always manage to reach a global consensus. This convergence is obtained after a time generically scaling with the population’s size N as tconv∼N1.4±0.1, i.e., much faster than for agents embedded on regular lattices. Moreover, the memory capacity required by the system scales only linearly with its size. Particular attention is given to heterogenous networks, in which the dynamical activity pattern of a node depends on its degree. High-degree nodes have a fundamental role, but require larger memory capacity. They govern the dynamics acting as spreaders of (linguistic) conventions. The effects of other properties, such as the average degree and the clustering, are also discussed
In-depth analysis of the Naming Game dynamics: the homogeneous mixing case
Language emergence and evolution has recently gained growing attention
through multi-agent models and mathematical frameworks to study their behavior.
Here we investigate further the Naming Game, a model able to account for the
emergence of a shared vocabulary of form-meaning associations through
social/cultural learning. Due to the simplicity of both the structure of the
agents and their interaction rules, the dynamics of this model can be analyzed
in great detail using numerical simulations and analytical arguments. This
paper first reviews some existing results and then presents a new overall
understanding.Comment: 30 pages, 19 figures (few in reduced definition). In press in IJMP
Information and Computation
In this chapter, concepts related to information and computation are reviewed
in the context of human computation. A brief introduction to information theory
and different types of computation is given. Two examples of human computation
systems, online social networks and Wikipedia, are used to illustrate how these
can be described and compared in terms of information and computation.Comment: 9 pages, 3 figures. Draft of a chapter to be published in Michelucci,
P. (Ed.) Handbook of Human Computation, Springe
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