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## Publications

Publications (65)

Generalized thermostatistical formalisms arising from extensions or generalizations of the standard logarithmic entropy are attracting considerable attention nowadays, specially associated with the study of complex systems. Probability distributions optimizing non-standard entropies are common in Nature and are observed in diverse types of complex...

In this paper, we describe a model for the automatic generation of literary sentences in French. Although there has been much recent effort directed towards automatic text generation in general, the generation of creative, literary sentences that is not restricted to a specific genre, which we approached in this work, is a difficult task that is no...

In this paper, we introduce a model for the automatic generation of literary sentences in French. It is based on algorithms that we have previously used to generate sentences in Spanish and Portuguese, and on a new corpus consisting of literary texts in French that we have constructed, called [FR]. Our automatic text generation algorithm combines l...

Several generalizations or extensions of the Boltzmann–Gibbs thermostatistics, based on non-standard entropies, have been the focus of considerable research activity in recent years. Among these, the power-law, non-additive entropies Sq≡k1−∑ipiqq−1(q∈R;S1=SBG≡−k∑ipilnpi) have harvested the largest number of successful applications. The specific str...

We present the section of the MegaLite corpus based on literary texts in Portuguese. This new section has been developed and adapted to be used for Computational Creativity tasks, such as Natural Language Processing, Automatic Text Generation (ATG), and other similar purposes. We highlight characteristics of the Portuguese section, such as the numb...

Systems consisting of confined, interacting particles doing overdamped motion admit an effective description in terms of nonlinear Fokker–Planck equations. The behavior of these systems is closely related to the [Formula: see text] power-law entropies and can be interpreted in terms of the [Formula: see text]-based thermostatistics. The connection...

Neural networks normally used to model associative memory can be regarded as consisting of dissipative units (the neurons) that interact in such a way that the network itself admits a global energy or Liapunov function. The network’s global dynamics is such that the system always evolves “downhill” in the energy landscape. In most models for associ...

Nonlinear diffusion and Fokker-Planck equations constitute valuable tools in the study of diverse phenomena in complex systems. Processes described by these equations are closely related to thermostatistical formalisms based on generalized entropic functionals. Inspired by these relations, we explore the behavior of systems of coupled, nonlinear Fo...

In recent years, researchers in the area of Computational Creativity have studied the human creative process proposing different approaches to reproduce it with a formal procedure. In this paper, we introduce a model for the generation of literary rhymes in Spanish, combining structures of language and neural network models %(\textit{Word2vec}).%,...

In recent years, researchers in the area of Computational Creativity have studied the human creative process proposing different approaches to reproduce it with a formal procedure. In this paper, we introduce a model for the generation of literary rhymes in Spanish, combining structures of language and neural network models The results obtained wit...

Distributions maximizing the \(S_q\) power-law entropies are observed in the behavior of complex systems arising in a remarkably wide range of disciplines, including neuroscience. One known effective description of processes leading to these maximum entropy distributions is provided by nonlinear, power-law Fokker–Planck equations. In this work, we...

Recently, Fagerholm, Friston, Moran and Leech advanced a class of linear neural network models complying with Lagrangean dynamics. In the present effort, we explore the possibility of extending the Lagrangean approach to nonlinear models. We present a Lagrangean formalism for a family of nonlinear neural network models, and investigate its main mat...

We investigate a one-dimensional, many-body system consisting of particles interacting via repulsive, short-range forces, and moving in an overdamped regime under the effect of a drag force that depends on direction. That is, particles moving to the right do not experience the same drag as those moving to the left. The dynamics of the system, effec...

Los algoritmos de Redes Neuronales son ampliamente utilizados en técnicas de Inteligencia Artificial (IA) para la resolución de problemas en diferentes campos de la ciencia que no pueden ser resueltos por la computación simbólica tradicional. En este trabajo, presentamos un conjunto de experimentos que involucran la implementación de varios modelos...

In this work we implement a mathematical model of synaptic transmission connecting neurons in a circuit of reverberating discharges in order to investigate its behavior in front of parametric variations. Using a program developed in C language, we verified if this model would behave as short-term memory circuit. In the simulation, we used neural pa...

In this work we implement a mathematical model of synaptic transmission connecting neurons in a circuit of reverberating discharges in order to investigate its behavior in front of parametric variations. Using a program developed in C language, we verified if this model would behave as short-term memory circuit. In the simulation, we used neural pa...

This paper presents an algorithm based on fuzzy logic, devised to identify emotions in corpora of literary texts, called Fuzzy Logic Emotions (FLE) classifier. This algorithm evaluates a sentence to define the class(es) of emotions to which it belongs. For this purpose, it considers three types of linguistic variables (verb, noun and adjective) wit...

Resumen: En este trabajo abordamos la generación automática de frases literarias en español. Proponemos un modelo de generación textual basado en algoritmos estadísticos y análisis sintáctico superficial. Presentamos resultados preliminares que son bastante alentadores. Palabras clave: Generación de texto, Modelos de lenguaje, Word embedding Abstra...

Distributions maximizing \(S_q\) entropies are not rare in Nature. They have been observed in complex systems in diverse fields, including neuroscience. Nonlinear Fokker-Planck dynamics constitutes one of the main mechanisms that can generate \(S_q\)-maximum entropy distributions. In the present work, we investigate a nonlinear Fokker-Planck equati...

Progress has been recently made, both theoretical and experimental, regarding the thermostatistics of complex systems of interacting particles or agents (species) obeying a nonlinear Fokker-Planck dynamics. However, major advances along these lines have been restricted to systems consisting of only one type of species. The aim of the present contri...

En este artı́culo abordamos el tema de la generación automática de frases literarias, que es una parte importante de los estudios relacionados al área de la Creatividad Computacional (CC). Proponemos tres modelos de generación textual guiados por un contexto, basados principalmente en algoritmos estadı́sticos y análisis sintáctico superficial. Los...

The area of Computational Creativity has received much attention in recent years. In this paper, within this framework, we propose a model for the generation of literary sentences in Spanish, which is based on statistical algorithms, shallow parsing and the automatic detection of personality features of characters of well known literary texts. We p...

We investigate the consequences of anisotropic drag forces for the thermostatistics of systems of interacting particles in the overdamped motion regime. Systems of confined particles interacting via short-range forces and performing overdamped motion exhibit interesting thermodynamic features, and constitute useful models for various problems in ph...

Nonlinear Fokker–Planck equations (NLFPEs) constitute useful effective descriptions of some interacting many-body systems. Important instances of these nonlinear evolution equations are closely related to the thermostatistics based on the S q power-law entropic functionals. Most applications of the connection between the NLFPE and the S q entropies...

In this work we present a state of the art in the area of Computational Creativity (CC). In particular, we address the automatic generation of literary sentences in Spanish. We propose three models of text generation based mainly on statistical algorithms and shallow parsing analysis. We also present some rather encouraging preliminary results.

The nonextensive thermostatistical formalism has been increasingly applied to the description of many complex systems in physics, biology, psychology, economics, and other fields. The q-Maximum Entropy (q-MaxEnt) distributions, which optimize the \(S_q\), power-law entropic functionals, are central to this formalism. We have done previous work rega...

Much of our recent work regards the development of schematic, neurocomputational models based on memory associativity to describe some processes associated with basic structures of mental functioning, such as neurosis, creativity, consciousness/unconsciousness, and psychoses. We have emphasized associative memory mechanisms, since they are central...

Diverse processes in statistical physics are usually analyzed on the assumption that the drag force acting on a test particle moving in a resisting medium is linear on the velocity of the particle. However, nonlinear drag forces do appear in relevant situations that are currently the focus of experimental and theoretical work. Motivated by these de...

q-Maximum Entropy (q-MaxEnt) distributions optimizing the \(S_q\), power-law entropic functionals are at the core of the nonextensive thermostatistical formalism. This formalism has been increasingly applied to the description of diverse complex systems in physics, biology, economics, and other fields. Previous work on computational neural models f...

We explore statistical characteristics of avalanches associated with the dynamics of a complex-network model, where two modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's ideas regarding the neuroses and that consciousness is related with symbolic...

We advance two nonlinear wave equations related to the nonextensive thermostatistical formalism based upon the power-law nonadditive Sq entropies. Our present contribution is in line with recent developments, where nonlinear extensions inspired on the q-thermostatistical formalism have been proposed for the Schroedinger, Klein-Gordon, and Dirac wav...

In previous work we have developed illustrative, neurocomputational models to describe mechanisms associated with mental processes. In these efforts, we have considered mental processes in phenomena such as neurosis, creativity, consciousness/unconsciousness, and some characteristics of the psychoses. Memory associativity is a key feature in the th...

Nonlinear Fokker-Planck equations endowed with curl drift forces are investigated. The conditions under which these evolution equations admit stationary solutions, which are $q$-exponentials of an appropriate potential function, are determined. It is proved that when these stationary solutions exist, the nonlinear Fokker-Planck equations satisfy an...

We studied the behavior of a mathematic-computational model for a reverberating neuronal circuit with controlled feedback, verifying the output pattern of the circuit, by means simulations using a program in language C++. Using values obtained from surveying the literature from
animal
experiments,
we observed that the model was able to reproduce t...

We review the contributions of some known models to the discussion of what the underlying neuronal mechanisms of consciousness creation should be. In particular, we note how different aspects of human mental behavior, such as in psychopathologies and dreams, may contribute to the understanding of these basic components. The interplay of conscious a...

We have studied the behavior of the electric potential profile across the membrane of the ganglion neuron and the neuroblastoma cell. We considered the physicochemical conditions during the resting and action potential (AP) states of the neuronal cells, and analyzed the influence of the fixed charges of the membrane on the surface electric potentia...

We have modeled the electric potential profile, across the membranes of the ganglion neuron and neuroblastoma cells. We consi-dered the resting and action potential states, and analyzed the influence of fixed charges of the membrane on the electric potential of the surface of the membranes of these cells, based on experimental values of mem-brane p...

We have previously described aspects of neurotic mental pathology, in terms of its relation to memory function and proposed a neural network model, whereby neurotic behavior is described as an associative memory process. Modules corresponding to sensory and symbolic memories interact, representing unconscious and conscious mental processes. Our mai...

In earlier work, we have proposed a neural network model that describes some mental processes involved in neuroses, by an
associative memory mechanism, where modules corresponding to sensorial and symbolic memories interact, representing unconscious
and conscious mental activity. Here, we relate our neuroses model with two models which have been pr...

We have previously described neurotic psychopathology and psychoanalytic working-through by an associative memory mechanism, based on a neural network. Memory was initially modelled by a Boltzmann machine (BM). We simulated known microscopic mechanisms that control synaptic properties and showed that the network self-organizes to a hierarchical, cl...

We review concepts introduced in earlier work, where a neural network mechanism describes some mental processes in neurotic pathology and psychoanalytic working-through, as associative memory functioning, according to the findings of Freud. We developed a complex network model, where modules corresponding to sensorial and symbolic memories interact...

We compare the use of Generalized Simulated Annealing (GSA) to the traditional Boltzmann Machine (BM), to model memory functioning,
in a neural network model that describes conscious and unconscious processes involved in neurosis, which we proposed in earlier
work. Modules corresponding to sensorial and symbolic memories interact, representing unco...

We have previously described the mental pathology known as neurosis, in terms of its relation to memory function. We proposed neural network mechanisms, whereby neurotic behavior is described as a brain associative memory process, and the symbolic associativity involved in psychoanalytic working-through can be mapped onto a corresponding network re...

Landauer's principle is fundamental for the physics of information. It establishes the least amount of energy that needs to be dissipated in order to erase a bit of information. Using the Beck–Cohen representation of statistical ensemble distributions, we explore an extension of Landauer's principle to systems out of equilibrium.

We have described the mental pathology known as neurosis, in terms of its re- lation to memory function and proposed neural network mechanisms, whereby neurotic behavior is described as a brain associative memory process. Micro- scopic mechanisms that control synaptic properties self organize the memory networks to a hierarchical, clustered structu...

We have previously described neurotic psychopathology and psychoanalytic
working-through by an associative memory mechanism, based on a neural
network model, where memory was modelled by a Boltzmann machine (BM).
Since brain neural topology is selectively structured, we simulated
known microscopic mechanisms that control synaptic properties, showin...

We proposed a mechanism in [1] whereby neurotic behavior may be understood as an associative memory process in the brain, and the symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neuronal network. Memory was modeled by a Boltzmann machine represented by a co...

In an earlier paper [1], we described the mental pathology known as neurosis in terms of its relation to memory function.
We proposed a mechanism whereby neurotic behavior may be understood as an associative memory process in the brain, and the
symbolic associative process involved in psychoanalytic working-through can be mapped onto a process of r...

We present a mathematical-computational model of the development of Alzheimer’s disease, based on the assumption that cholesterol
plays a key role in the formation of neuropathological lesions that characterize the disease: the senile amyloid plaques and
neurofibrillary tangles. The final model, conceived as a system of equations, was simulated by...

We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a
neurocomputational substrate. These models are examples of real world complex networks with interesting general topological
structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system,...

Since little is still known about fundamental brain mechanisms associated to thought, its different manifestations are usually classified in an oversimplified way into normal and abnormal, like delusional and disorganized thought or creative thinking. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, and th...

Since little is still known about fundamental brain mechanisms associated to thought, its different manifestations are usually classified in an oversimplified way into normal and abnormal, like delusional and disorganized thought or creative thinking. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, and th...

Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose a schematic self-organizing
neural network model, to explain development of cortical map structure and dynamics of memory access, and unify different
mental processes into a single neurocomputational substrate. Based on our neural network model, n...

Since little is still known about fundamental brain mechanisms associated to thought, its different manifestations are usually
classified in an oversimplified way into normal and abnormal, like delusional and disorganized thought or creative thinking.
Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, and th...

In an earlier paper (17), we described the mental patho- logy known as neurosis in terms of its relation to memory function. We proposed, based on a neural network model, that neurotic behavior may be understood as an associative memory process in the brain, and that the symbolic asso- ciative process involved in psychoanalytic working-through can...

Analysing and debugging parallel and distributed pro-grams is usually a difficult and not well explored problem. This is largely due to the non-deterministic nature of the run-time states of these processes, and results in a general lack of adequate parallel debugging tools. In this paper, we present solutions for the problem of detecting global ge...

Some physical systems need to be modeled for simulation so that they evolve in time in both a time-driven (time-stepped) and an event-driven manner. An example is a system of colliding particles that move in a dynamically changing potential field. Such behavior can be observed in the modeling of real physical systems such as nuclear collisions and...

We have developed a distributed algorithm for the simulation of systems that evolve continuously, but which are also subject to discrete events that affect their evolution. As an example we consider the description through the BUU equations of the time evolution of a highly excited nuclear system, and show that this algorithm attains almost optimal...

We study the relativistic p+Ag collision using an intranuclear cascade model that includes some mean-field effects. The time evolution of the energy distribution and size of the system indicates that it reaches thermal equilibrium prior to its fragmentation.

Since little is still known about brain mechanisms associated to thought, its manifestations are usually classified in an oversimplified way into categories, like delusional and disorganized thought or creative thinking. We seek a better understanding of some conscious and unconscious mental phenomena, describing them as the evolution of emergent s...