Prof. Vittorio Loreto

The reconstruction of phylogenies of cultural artefacts represents an open problem that mixes theoretical and computational challenges. Existing bench- marks rely on simulated phylogenies, where hypotheses on the underlying evolutionary mechanisms are unavoidable, or in real data phylogenies, for which no true evolutionary history is known. Here we introduce a web-based game, Copystree, where users create phylogenies of manuscripts, through successive copying actions, in a fully monitored setup. While players enjoy the experience, Copystree allows to build artificial phylogenies whose evolutionary processes do not obey to any pre-defined theoretical mechanisms, being generated instead with the unpredictability of human creativity. We present the analysis of the data gathered during the first set of experiments and use the artificial phylogenies gathered for a first test of existing phylogenetic algorithms.

The emergence of novelties and their rise and fall
in popularity is an ubiquitous phenomenon in human
activities. The coexistence of always popular
milestones with novel and sometimes ephemeral trends
pervades technological, scientific and artistic
production. By introducing suitable statistical
measures, we demonstrate that different systems of
human activities, i.e. the creation of hashtags in
Twitter, the interaction with online program code
repositories, the creation of texts and the
listening of songs on an on-line platform, exhibit
surprisingly similar properties. We then introduce
a general framework to explain those
regularities. We propose a simple mathematical model
based on the expansion into the adjacent possible,
that has been proven to be a very general and
powerful mechanism able to explain many of the
statistical patterns emerging in innovation
dynamics, to which we add two crucial elements. On
the one hand we quantify the idea that, while
exploring a conceptual or physical space, inertia
exists towards known already discovered elements. On
the other hand, we highlight the role of the
collective dynamics – where many users interact, in
a direct or indirect way in the emergence and
diffusion of novelties and innovations.

Rules are an efficient feature of natural languages
which allow speakers to use a finite set of
instructions to generate a virtually infinite set of
utterances. Yet, for many regular rules, there are
irregular exceptions. There has been lively debate
in cognitive science about how individual learners
acquire rules and exceptions; for example, how they
learn the past tense of preach is preached, but for
teach it is taught. However, for most population or
language-level models of language structure,
particularly from the perspective of language
evolution, the goal has generally been to examine
how languages evolve stable structure, and neglects
the fact that in many cases, languages exhibit
exceptions to structural rules. We examine the
dynamics of regularity and irregularity across a
population of interacting agents to investigate how,
for example, the irregular teach coexists beside the
regular preach in a dynamic language system. Models
show that in the absence of individual biases
towards either regularity or irregularity, the
outcome of a system is determined entirely by the
initial condition. On the other hand, in the
presence of individual biases, rule systems exhibit
frequency dependent patterns in regularity
reminiscent of patterns found in natural
language. We implement individual biases towards
regularity in two ways: through ?child? agents who
have a preference to generalise using the regular
form, and through a memory constraint wherein an
agent can only remember an irregular form for a
finite time period. We provide theoretical arguments
for the prediction of a critical frequency below
which irregularity cannot persist in terms of the
duration of the finite time period which constrains
agent memory. Further, within our framework we also
find stable irregularity, arguably a feature of most
natural languages not accounted for in many other
cultural models of language structure.

It is common opinion that many innovations are
triggered by serendipity whose notion is associated
with fortuitous events leading to unintended
consequences. One might argue that this
interpretation is due to the poor understanding of
the dynamics of innovations. Very little is known,
in fact, about how innovations proceed and samples
the space of potential novelties. This space is
usually referred to as the adjacent possible, a
concept originally introduced in the study of
biological systems to indicate the set of
possibilities that are one step away from what
actually exists. In this paper we focus on the
problem of defining the adjacent possible space, and
analyzing its dynamics, for a particular system,
namely the cultural system of the network of movies.
We synthesized to this end the graph emerging from
the Internet Movies Database (IMDb) and looked at
the static and dynamical properties of this
network. We deal, in particular, with the subtle
mechanism of the adjacent possible by measuring the
expansion and the coverage of this elusive space
during the global evolution of the system. Finally,
we introduce the concept of adjacent possibilities
at the level of single node and try to elucidate its
nature by looking at the correlations with
topological and user annotation metrics.

The dynamics of political votes has been widely
studied, both for its practical interest and as a
paradigm of the dynamics of mass opinions and
collective phenomena, where theoretical predictions
can be easily tested. However, the vote outcome is
often influenced by many factors beyond the bare
opinion on the candidate, and in most cases it is
bound to a single preference. The voter perception
of the political space is still to be elucidated. We
here propose a web experiment (laPENSOcos`ı) where
we explicitly investigate participants’ opinions on
political entities (parties, coalitions, individual
candidates) of the Italian political scene. As a
main result, we show that the political perception
follows a Weber-Fechner-like law, i.e., when ranking
political entities according to the user expressed
preferences, the perceived distance of the user from
a given entity scales as the logarithm of this
rank.

Rules are an efficient feature of natural languages
which allow speakers to use a finite set of
instructions to generate a virtually infinite set of
utterances. Yet, for many regular rules, there are
irregular exceptions. There has been lively debate
in cognitive science about how individual learners
acquire rules and exceptions; for example, how they
learn the past tense of preach is preached, but for
teach it is taught. In this paper, we take a
different perspective, examining the dynamics of
regularity and irregularity across a population of
interacting agents to investigate how inflectional
rules are applied to verbs. We show that in the
absence of biases towards either regularity or
irregularity, the outcome is determined by the
initial condition, irrespective of the frequency of
usage of the given lemma. On the other hand, in
presence of biases, rule systems exhibit frequency
dependent patterns in regularity reminiscent of
patterns in natural language corpora. We examine the
case where individuals are biased towards linguistic
regularity in two ways: either as child learners, or
through a memory constraint wherein irregular forms
can only be remembered by an individual agent for a
finite time period. We provide theoretical arguments
for the prediction of a critical frequency below
which irregularity cannot persist in terms of the
duration of the finite time period which constrains
agent memory.

Studies in literature and narrative have begun to
argue more forcefully for considering human
evolution as central to understanding stories and
storytelling more generally (Sugiyama, 2001;
Hernadi, 2002). However, empirical studies in
language evolution have focused primarily on
language structure or the language faculty, leaving
the evolution of stories largely unexplored
(although see Von Heiseler, 2014). Stories are
unique products of human culture enabled principally
by human language. Given this, the dynamics of
creativity in stories, and the traits which make
successful stories, are of crucial interest to
understanding the evolution of language in the
context of human evolution more broadly. The current
work aims to illuminate how stories emerge, evolve,
and change in the context of a collaborative
cultural effort. We present results from a novel
experimental paradigm centered around a story game
where players write short continuations (between 60
and 120 characters) of existing stories. These
continuations then become open to other players to
continue in turn. Stories are subject to player
selection, allowing for variation and speciation of
the resulting narratives, and evolve as a result of
collaborative effort between players. The game
starts with a seed of over 60 potential stories, and
players choose which stories to continue, providing
a player-driven story selection mechanism. In this
way, stories which are creative, intriguing, and
open ended spawn more stories, and eventually lead
to longer story paths as play continues. The game
also introduces further limitations by constraining
a players’�� view of the story path: players have
access only to a story and its parent, meaning
knowledge of the existing narrative is limited. We
present data from hundreds of players and stories,
creating large story trees which explore the space
of different possible narratives which grow out of a
confined set of starting points. This data allows us
to investigate several aspects of the growing story
trees to illuminate not only what makes a story
successful, but how creative stories trigger new
stories, and what makes individual storytellers
successful. Given the selection mechanism central to
game play, we identify the most successful stories
by their number of offspring. Particularly
successful storytellers emerge measured both by how
many children their stories have spawned, and also
how long their story path extends. We also show that
coherent stories often emerge, despite the fact that
they are authored by several different players, and
any given player only sees a limited snapshot of the
story path. We contextualise the results of the game
and connect it to language evolution in two
ways. First, we look for detectable triggers of
innovation and creativity within the story trees,
and identify these as expanding the adjacent
possible (e.g., new adaptations open the space of
other possible adaptations in the future; Tria,
Loreto, Servedio, & Strogatz, 2014). We argue that
this concept can be extended to stories, using
evidence from the game bolstered by evidence from
more traditional literature (the Gutenberg
Corpus). Second, we frame the results in terms of
recurring themes found in storytelling
cross-culturally (Tehrani, 2013). We suggest that
the most successful triggers of innovation in
stories combine original novelty and a firm
grounding in existing recurring story frameworks in
human culture. This indicates that much like other
cultural and biological systems, stories are subject
to competing pressures for stability and
conservation on the one hand, and innovation and
novelty on the other.

Creole languages offer an invaluable opportunity to
study the processes leading to the emergence and
evolution of Language, thanks to the short –
typically a few generations – and reasonably well
defined time-scales involved in their
emergence. Another well-known case of a very fast
emergence of a Language, though referring to a much
smaller population size and different ecological
conditions, is that of the Nicaraguan Sign
Language. What these two phenomena have in common is
that in both cases what is emerging is a contact
language, i.e., a language born out of the
non-trivial interaction of two (or more) parent
languages. This is a typical case of what is known
in biology as horizontal transmission. In many
well-documented cases, creoles emerged in large
segregated sugarcane or rice plantations on which
the slave labourers were the overwhelming
majority. Lacking a common substrate language,
slaves were naturally brought to shift to the
economically and politically dominant European
language (often referred to as the lexifier) to
bootstrap an effective communication system among
themselves. Here, we focus on the emergence of
creole languages originated in the contacts of
European colonists and slaves during the 17th and
18th centuries in exogenous plantation colonies of
especially the Atlantic and Indian Ocean, where
detailed census data are available. Those for
several States of USA can be found at
http://www.census.gov/history, while for Central
America and the Caribbean can be found at
http://www.jamaicanfamilysearch.com/Samples/1790al11.htm. Without
entering in the details of the creole formation at a
fine-grained linguistic level, we aim at uncovering
some of the general mechanisms that determine the
emergence of contact languages, and that
successfully apply to the case of creole formation.

The complex organization of syntax in hierarchical
structures is one of the core design features of
human language. Duality of patterning refers for
instance to the organization of the meaningful
elements in a language at two distinct levels: a
combinatorial level where meaningless forms are
combined into meaningful forms and a compositional
level where meaningful forms are composed into
larger lexical units. The question remains wide open
regarding how such a structure could have
emerged. Furthermore a clear mathematical framework
to quantify this phenomenon is still lacking. The
aim of this paper is that of addressing these two
aspects in a self-consistent way. First, we
introduce suitable measures to quantify the level of
combinatoriality and compositionality in a language,
and present a framework to estimate these
observables in human natural languages. Second, we
show that the theoretical predictions of a
multi-agents modeling scheme, namely the Blending
Game, are in surprisingly good agreement with
empirical data. In the Blending Game a population of
individuals plays language games aiming at success
in communication. It is remarkable that the two
sides of duality of patterning emerge simultaneously
as a consequence of a pure cultural dynamics in a
simulated environment that contains meaningful
relations, provided a simple constraint on message
transmission fidelity is also considered.

The understanding and the characterisation of
individual mobility patterns in urban environments
is important in order to improve liveability and
planning of big cities. In relatively recent times,
the availability of data regarding human movements
have fostered the emergence of a new branch of
social studies, with the aim to unveil and study
those patterns thanks to data collected by means of
geolocalisation technologies. In this paper we
analyse a large dataset of GPS tracks of cars
collected in Rome (Italy). Dividing the drivers in
classes according to the number of trips they
perform in a day, we show that the sequence of the
travelled space connecting two consecutive stops
shows a precise behaviour so that the shortest trips
are performed at the middle of the sequence, when
the longest occur at the beginning and at the end
when drivers head back home. We show that this
behaviour is consistent with the idea of an
optimisation process in which the total travel time
is minimised, under the effect of spatial
constraints so that the starting points is on the
border of the space in which the dynamics takes
place.

Empirical evidence shows that the rate of irregular
usage of English verbs exhibits discontinuity as a
function of their frequency: the most frequent verbs
tend to be totally irregular. We aim to
qualitatively understand the origin of this feature
by studying simple agent-based models of language
dynamics, where each agent adopts an inflectional
state for a verb and may change it upon interaction
with other agents. At the same time, agents are
replaced at some rate by new agents adopting the
regular form. In models with only two inflectional
states (regular and irregular), we observe that
either all verbs regularise irrespective of their
frequency, or a continuous transition occurs between
a low-frequency state, where the lemma becomes fully
regular, and a high-frequency one, where both forms
coexist. Introducing a third (mixed) state, wherein
agents may use either form, we find that a third,
qualitatively different behaviour may emerge,
namely, a discontinuous transition in frequency. We
introduce and solve analytically a very general
class of three-state models that allows us to fully
understand these behaviours in a unified
framework. Realistic sets of interaction rules,
including the well-known naming game (NG) model,
result in a discontinuous transition, in agreement
with recent empirical findings. We also point out
that the distinction between speaker and hearer in
the interaction has no effect on the collective
behaviour. The results for the general three-state
model, although discussed in terms of language
dynamics, are widely applicable.

Several recent theories have suggested that an
increase in the number of non-native speakers in a
language can lead to changes in morphological
rules. We examine this experimentally by contrasting
the performance of native and non-native English
speakers in a simple Wug-task, showing that
non-native speakers are significantly more likely to
provide non -ed (i.e., irregular) past-tense forms
for novel verbs than native speakers. Both groups
are sensitive to sound similarities between new
words and existing words (i.e., are more likely to
provide irregular forms for novel words which sound
similar to existing irregulars). Among both natives
and non-natives, irregularizations are non-random;
that is, rather than presenting as truly irregular
inflectional strategies, they follow identifiable
sub-rules present in the highly frequent set of
irregular English verbs. Our results shed new light
on how native and non-native learners can affect
language structure.

The comprehension of vehicular traffic in urban
environments is crucial to achieve a good management
of the complex processes arising from people
collective motion. Even allowing for the great
complexity of human beings, human behavior turns out
to be subject to strong constraints—physical,
environmental, social, economic—that induce the
emergence of common patterns. The observation and
understanding of those patterns is key to setup
effective strategies to optimize the quality of life
in cities while not frustrating the natural need for
mobility. In this paper we focus on vehicular
mobility with the aim to reveal the underlying
patterns and uncover the human strategies
determining them. To this end we analyze a large
dataset of GPS vehicles tracks collected in the Rome
(Italy) district during a month. We demonstrate the
existence of a local optimization of travel times
that vehicle drivers perform while choosing their
journey. This finding is mirrored by two additional
important facts, i.e., the observation that the
average vehicle velocity increases by increasing the
travel length and the emergence of a universal
scaling law for the distribution of travel times at
fixed traveled length. A simple modeling scheme
confirms this scenario opening the way to further
predictions.

Language universals have long been attributed to an
innate Universal Grammar. An alternative explanation
states that linguistic universals emerged
independently in every language in response to
shared cognitive or perceptual biases. A
computational model has recently shown how this
could be the case, focusing on the paradigmatic
example of the universal properties of colour naming
patterns, and producing results in quantitative
agreement with the experimental data. Here we
investigate the role of an individual perceptual
bias in the framework of the model. We study how,
and to what extent, the structure of the bias
influences the corresponding linguistic universal
patterns. We show that the cultural history of a
group of speakers introduces population-specific
constraints that act against the pressure for
uniformity arising from the individual bias, and we
clarify the interplay between these two forces

We introduce a model for music generation where
melodies are seen as a network of interacting
notes. Starting from the principle of maximum
entropy we assign to this network a probability
distribution, which is learned from an existing
musical corpus. We use this model to generate novel
musical sequences that mimic the style of the
corpus. Our main result is that this model can
reproduce high-order patterns despite having a
polynomial sample complexity. This is in contrast
with the more traditionally used Markov models that
have an exponential sample complexity.

Contact languages are born out of the non-trivial
interaction of two (or more) parent
languages. Nowadays, the enhanced possibility of
mobility and communication allows for a strong
mixing of languages and cultures, thus raising the
issue of whether there are any pure languages or
cultures that are unaffected by contact with
others. As with bacteria or viruses in biological
evolution, the evolution of languages is marked by
horizontal transmission; but to date no reliable
quantitative tools to investigate these phenomena
have been available. An interesting and well
documented example of contact language is the
emergence of creole languages, which originated in
the contacts of European colonists and slaves during
the 17th and 18th centuries in exogenous plantation
colonies of especially the Atlantic and Indian
Ocean. Here, we focus on the emergence of creole
languages to demonstrate a dynamical process that
mimics the process of creole formation in American
and Caribbean plantation ecologies. Inspired by the
Naming Game (NG), our modeling scheme incorporates
demographic information about the colonial
population in the framework of a non-trivial
interaction network including three populations:
Europeans, Mulattos/Creoles, and Bozal slaves. We
show how this sole information makes it possible to
discriminate territories that produced modern
creoles from those that did not, with a surprising
accuracy. The generality of our approach provides
valuable insights for further studies on the
emergence of languages in contact ecologies as well
as to test specific hypotheses about the peopling
and the population structures of the relevant
territories. We submit that these tools could be
relevant to addressing problems related to contact
phenomena in many cultural domains: e.g., emergence
of dialects, language competition and hybridization,
globalization phenomena.

Human languages are rule governed, but almost
invariably these rules have exceptions in the form
of irregularities. Since rules in language are
efficient and productive, the persistence of
irregularity is an anomaly. How does irregularity
linger in the face of internal (endogenous) and
external (exogenous) pressures to conform to a rule?
Here we address this problem by taking a detailed
look at simple past tense verbs in the Corpus of
Historical American English. The data show that the
language is open, with many new verbs entering. At
the same time, existing verbs might tend to
regularize or irregularize as a consequence of
internal dynamics, but overall, the amount of
irregularity sustained by the language stays roughly
constant over time. Despite continuous vocabulary
growth, and presumably, an attendant increase in
expressive power, there is no corresponding growth
in irregularity. We analyze the set of irregulars,
showing they may adhere to a set of minority rules,
allowing for increased stability of irregularity
over time. These findings contribute to the debate
on how language systems become rule governed, and
how and why they sustain exceptions to rules,
providing insight into the interplay between the
emergence and maintenance of rules and exceptions in
language.

The naming game (NG) describes the agreement
dynamics of a population of N agents interacting
locally in pairs leading to the emergence of a
shared vocabulary. This model has its relevance in
the novel fields of semiotic dynamics and
specifically to opinion formation and language
evolution. The application of this model ranges from
wireless sensor networks as spreading algorithms,
leader election algorithms to user-based social
tagging systems. In this paper, we introduce the
concept of overhearing (i.e., at every time step of
the game, a random set of N-delta individuals are
chosen from the population who overhear the
transmitted word from the speaker and accordingly
reshape their inventories). When delta = 0 one
recovers the behavior of the original NG. As one
increases delta, the population of agents reaches a
faster agreement with a significantly low-memory
requirement. The convergence time to reach global
consensus scales as log N as delta approaches
1. Copyright (C) EPLA, 2013

The lexicons of human languages organize their units
at two distinct levels. At a first combinatorial
level, meaningless forms (typically referred to as
phonemes) are combined into meaningful units
(typically referred to as morphemes). Thanks to
this, many morphemes can be obtained by relatively
simple combinations of a small number of
phonemes. At a second compositional level of the
lexicon, morphemes are composed into larger lexical
units, the meaning of which is related to the
individual meanings of the composing morphemes. This
duality of patterning is not a necessity for
lexicons and the question remains wide open
regarding how a population of individuals is able to
bootstrap such a structure and the evolutionary
advantages of its emergence. Here we address this
question in the framework of a multi-agents model,
where a population of individuals plays simple
naming games in a conceptual environment modeled as
a graph. We demonstrate that errors in communication
as well as a blending repair strategy, which
crucially exploits a shared conceptual
representation of the environment, are sufficient
conditions for the emergence of duality of
patterning, that can thus be explained in a pure
cultural way. Compositional lexicons turn out to be
faster to lead to successful communication than
purely combinatorial lexicons, suggesting that
meaning played a crucial role in the evolution of
language.

One of the fundamental problems in cognitive science
is how humans categorize the visible color
spectrum. The empirical evidence of the existence of
universal or recurrent patterns in color naming
across cultures is paralleled by the observation
that color names begin to be used by individual
cultures in a relatively fixed order. The origin of
this hierarchy is largely unexplained. Here we
resort to multiagent simulations, where a population
of individuals, subject to a simple perceptual
constraint shared by all humans, namely the human
Just Noticeable Difference, categorizes and names
colors through a purely cultural negotiation in the
form of language games. We found that the time
needed for a population to reach consensus on a
color name depends on the region of the visible
color spectrum. If color spectrum regions are ranked
according to this criterion, a hierarchy with [red,
(magenta)-red], [violet], [green/yellow], [blue],
[orange], and [cyan], appearing in this order, is
recovered, featuring an excellent quantitative
agreement with the empirical observations of the
WCS. Our results demonstrate a clear possible route
to the emergence of hierarchical color categories,
confirming that the theoretical modeling in this
area has now attained the required maturity to make
significant contributions to the ongoing debates
concerning language universals.

The empirical evidence that human color
categorization exhibits some universal patterns
beyond superficial discrepancies across different
cultures is a major breakthrough in cognitive
science. As observed in the World Color Survey
(WCS), indeed, any two groups of individuals develop
quite different categorization patterns, but some
universal properties can be identified by a
statistical analysis over a large number of
populations. Here, we reproduce the WCS in a
numerical model in which different populations
develop independently their own categorization
systems by playing elementary language games. We
find that a simple perceptual constraint shared by
all humans, namely the human Just Noticeable
Difference (JND), is sufficient to trigger the
emergence of universal patterns that unconstrained
cultural interaction fails to produce. We test the
results of our experiment against real data by
performing the same statistical analysis proposed to
quantify the universal tendencies shown in the WCS
[Kay P & Regier T. (2003) Proc. Natl. Acad. Sci. USA
100: 9085-9089], and obtain an excellent
quantitative agreement. This work confirms that
synthetic modeling has nowadays reached the maturity
to contribute significantly to the ongoing debate in
cognitive science.

Our social behaviour has evolved primarily through contact with a limited number of other individuals. Yet as a species we exhibit uniformities on a global scale. This kind of emergent behaviour is familiar territory for statistical physicists.

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 analyse 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 through 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 timescale of collective behaviours,
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.