Search results for: Araceli Sanchis

Items from 1 to 20 out of 56 results

article

Adaptive dialogue management using intent clustering and fuzzy rules

David Griol, Zoraida Callejas, Jose Manuel Molina, Araceli Sanchis

Conversational systems have become an element of everyday life for billions of users who use speech‐based interfaces to services, engage with personal digital assistants on smartphones, social media chatbots, or smart speakers. One of the most complex tasks in the development of these systems is to design the dialogue model, the logic that provided a user input selects the next answer. The dialogue...

article

A multimodal conversational coach for active ageing based on sentient computing and m‐health

David Griol, José Manuel Molina, Araceli Sanchis

Expert Systems > 37 > 2 > n/a - n/a

As life expectancy increases, it has become more necessary to find ways to support healthy ageing. A number of active ageing initiatives are being developed nowadays to foster healthy habits in the population. This paper presents our contribution to these initiatives in the form of a multimodal conversational coach that acts as a coach for physical activities. The agent can be developed as an Android...

chapter

Evolving Cauchy possibilistic clustering based on cosine similarity for monitoring cyber systems

Igor Skrjanc, Araceli Sanchis de Miguel, Jose Antonio Iglesias, Agapito Ledezma, more

2017 Evolving and Adaptive Intelligent Systems (EAIS) > 1 - 5

2017 Evolving and Adaptive Intelligent Systems (EAIS)

In this paper the idea of evolving Cauchy clustering based on cosine similarity is given. It is used for monitoring in the case of cyber attacks. The proposed idea is for that kind of processes very interesting because it is very efficient when the data are noisy and when the outliers appear frequently and this is the case when dealing with cyber attacks data. The algorithm is given in an evolving...

chapter

Monitoring of vulcano Puracé through seismic signals: Description of a real dataset

Jose Eduardo Gomez, David Camilo Corrales, Juan Carlos Corrales, Araceli Sanchis, more

2017 Evolving and Adaptive Intelligent Systems (EAIS) > 1 - 6

2017 Evolving and Adaptive Intelligent Systems (EAIS)

In this paper we present a large set of data obtained from the volcanic surveillance of Puracé volcano (in Colombia). The proposed data are the result of the real-time data from the seismological stations which are close to this volcano. These data are extracted from the Colombian Geological Survey (SGC) and we have processed all of them in order to create the proposed dataset. This dataset will help...

article

Cybernetics of the Mind: Learning Individual's Perceptions Autonomously

Plamen Angelov, Xiaowei Gu, Jose A. Iglesias, Agapito Ledezma, more

IEEE Systems, Man, and Cybernetics Magazine > 2017 > 3 > 2 > 6 - 17

In this article, we describe an approach to computational modeling and autonomous learning of the perception of sensory inputs by individuals. A hierarchical process of summarization of heterogeneous raw data is proposed. At the lower level of the hierarchy, the raw data autonomously form semantically meaningful concepts. Instead of clustering based on visual or audio similarity, the concepts are...

chapter

Genetic Programming for Predicting Protein Networks

Beatriz Garcia, Ricardo Aler, Agapito Ledezma, Araceli Sanchis

Lecture Notes in Computer Science > Advances in Artificial Intelligence – IBERAMIA 2008 > Applications > 432-441

One of the definitely unsolved main problems in molecular biology is the protein-protein functional association prediction problem. Genetic Programming (GP) is applied to this domain. GP evolves an expression, equivalent to a binary classifier, which predicts if a given pair of proteins interacts. We take advantages of GP flexibility, particularly, the possibility of defining new operations. In this...

chapter

Social network analysis: Evolving Twitter mining

Jose Antonio Iglesias, Aaron Garcia-Cuerva, Agapito Ledezma, Araceli Sanchis

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC) > 1809 - 1814

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The growth of techniques of social network analysis is fast at present. These techniques are of interest to many researchers in different areas such as sociology, communication and computer science, social psychologist and so on. Nowadays, by analyzing how the members of network interact, share information or establish relationships, useful knowledge about them and their relations can be extracted...

chapter

Forecasting time series by an ensemble of Artificial Neural Networks based on transforming the time series

German Gutierrez, M. Paz Sesmero, Araceli Sanchis

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC) > 4769 - 4774

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Times series forecasting issue can be found in several subject areas as finance and business (e.g. foreign exchange rates, data for prices), industry (energy load and demand), climate and meteorology (e.g. sea surface temperature and El Nio phenomenon), health (e.g. prognosis from medical data) and many others. This paper is focused in univariate time series (x₁, x₂, …, x_t), so unknown future values...

chapter

Sequential classifiers for network intrusion detection based on data selection process

David Camilo Corrales, Juan Carlos Corrales, Araceli Sanchis, Agapito Ledezma

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC) > 1827 - 1832

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

With the emergence of large datasets in real-time applications as network intrusion detection, systems classification have gained more attention due to the importance of these applications and the increasing generation of these network traffic information. The proliferation of Internet and networking applications, coupled with the widespread availability of system hacks and viruses have increased...

chapter

Autonomous Data Density based clustering method

Plamen P. Angelov, Xiaowei Gu, German Gutierrez, Jose Antonio Iglesias, more

2016 International Joint Conference on Neural Networks (IJCNN) > 2405 - 2413

2016 International Joint Conference on Neural Networks (IJCNN)

It is well known that clustering is an unsupervised machine learning technique. However, most of the clustering methods need setting several parameters such as number of clusters, shape of clusters, or other user- or problem-specific parameters and thresholds. In this paper, we propose a new clustering approach which is fully autonomous, in the sense that it does not require parameters to be pre-defined...

chapter

Predicting Opponent Actions by Observation

Agapito Ledezma, Ricardo Aler, Araceli Sanchis, Daniel Borrajo

Lecture Notes in Computer Science > RoboCup 2004: Robot Soccer World Cup VIII > Full Papers > 286-296

In competitive domains, the knowledge about the opponent can give players a clear advantage. This idea lead us in the past to propose an approach to acquire models of opponents, based only on the observation of their input-output behavior. If opponent outputs could be accessed directly, a model can be constructed by feeding a machine learning method with traces of the opponent. However, that is not...

chapter

Applying evolution strategies to neural networks robot controller

Antonio Berlanga, José M. Molina, Araceli Sanchis, Pedro Isasi

Lecture Notes in Computer Science > Engineering Applications of Bio-Inspired Artificial Neural Networks > 516-525

In this paper an evolution strategy (ES) is introduced, to learn weights of a neural network controller in autonomous robots. An ES is used to learn high-performance reactive behavior for navigation and collisions avoidance. The learned behavior is able to solve the problem in different environments; so, the learning process has proven the ability to obtain a specialized behavior. All the behaviors...

chapter

Sequence Classification Using Statistical Pattern Recognition

José Antonio Iglesias, Agapito Ledezma, Araceli Sanchis

Lecture Notes in Computer Science > Advances in Intelligent Data Analysis VII > Sequence/ Time Series Analysis > 207-218

Sequence classification is a significant problem that arises in many different real-world applications. The purpose of a sequence classifier is to assign a class label to a given sequence. Also, to obtain the pattern that characterizes the sequence is usually very useful. In this paper, a technique to discover a pattern from a given sequence is presented followed by a general novel method to classify...

chapter

Creating User Profiles from a Command-Line Interface: A Statistical Approach

José Antonio Iglesias, Agapito Ledezma, Araceli Sanchis

Lecture Notes in Computer Science > User Modeling, Adaptation, and Personalization > Peer-reviewed Papers > 90-101

Knowledge about computer users is very beneficial for assisting them, predicting their future actions or detecting masqueraders. In this paper, an approach for creating and recognizing automatically the behavior profile of a user from the commands (s)he types in a command-line interface, is presented. Specifically, in this research, a computer user behavior is represented as a sequence of UNIX...

chapter

Time Series Forecasting by Evolving Artificial Neural Networks Using “Shuffle”, Cross-Validation and Ensembles

Juan Peralta, German Gutierrez, Araceli Sanchis

Lecture Notes in Computer Science > Artificial Neural Networks – ICANN 2010 > ANN Applications > 50-53

Accurate time series forecasting are important for several business, research, and application of engineering systems. Evolutionary Neural Networks are particularly appealing because of their ability to design, in an automatic way, a model (an Artificial Neural Network) for an unspecified non-linear relationship for time series values. This paper evaluates two methods to obtain the pattern sets that...

chapter

Generative Capacities of Cellular Automata Codification for Evolution of NN Codification

Germán Gutiérrez, Inés M. Galván, José M. Molina, Araceli Sanchis

Lecture Notes in Computer Science > Artificial Neural Networks — ICANN 2002 > Connectionist Cognitive Science > 314-319

Automatic methods for designing artificial neural nets are desired to avoid the laborious and erratically human expert’s job. Evolutionary computation has been used as a search technique to find appropriate NN architectures. Direct and indirect encoding methods are used to codify the net architecture into the chromosome. A reformulation of an indirect encoding method, based on two bi-dimensional cellular...

chapter

Modeling Consciousness for Autonomous Robot Exploration

Raúl Arrabales Moreno, Agapito Ledezma Espino, Araceli Sanchis de Miguel

Lecture Notes in Computer Science > Bio-inspired Modeling of Cognitive Tasks > 51-60

This work aims to describe the application of a novel machine consciousness model to a particular problem of unknown environment exploration. This relatively simple problem is analyzed from the point of view of the possible benefits that cognitive capabilities like attention, environment awareness and emotional learning can offer. The model we have developed integrates these concepts into a situated...

chapter

A Comparing Method of Two Team Behaviours in the Simulation Coach Competition

José Antonio Iglesias, Agapito Ledezma, Araceli Sanchis

Lecture Notes in Computer Science > Modeling Decisions for Artificial Intelligence > Regular Papers > 117-128

The main goal of agent modelling is to extract and represent the knowledge about the behaviour of other agents. Nowadays, modelling an agent in multi-agent systems is increasingly becoming more complex and significant. Also, robotic soccer domain is an interesting environment where agent modelling can be used. In this paper, we present an approach to classify and compare the behaviour of a multi-agent...

chapter

Learning symbolic rules with a reactive with tags classifier system in robot navigation

Araceli Sanchis, José M. Molina, Pedro Isasi, Javier Segovia

Lecture Notes in Computer Science > Engineering Applications of Bio-Inspired Artificial Neural Networks > 548-557

Classifier System are special production systems where conditions and actions are codified in order to learn new rules by means of Genetic Algorithms (GA). These systems combine the execution capabilities of symbolic systems and the learning capabilities of Genetic Algorithms. The Reactive with Tags Classifier System (RTCS) is able to learn symbolic rules that allow to generate sequence of actions,...

chapter

Studying the Capacity of Grammatical Encoding to Generate FNN Architectures

Germán Gutiérrez, Beatriz García, José M. Molina, Araceli Sanchis

Lecture Notes in Computer Science > Computational Methods in Neural Modeling > Self-Organizing Systems > 478-485

Many methods to codify Artificial Neural Networks have been developed to avoid the defects of direct encoding schema, improving the search into the solution’s space. A method to estimate how the search space is covered and how are the movements along search process applying genetic operators is needed in order to evaluate the different encoding strategies for Feedforward Neural Networks. A first step...

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INFONA - science communication portal

Search results for: Araceli Sanchis

Adaptive dialogue management using intent clustering and fuzzy rules

A multimodal conversational coach for active ageing based on sentient computing and m‐health

Evolving Cauchy possibilistic clustering based on cosine similarity for monitoring cyber systems

Monitoring of vulcano Puracé through seismic signals: Description of a real dataset

Cybernetics of the Mind: Learning Individual's Perceptions Autonomously

Genetic Programming for Predicting Protein Networks

Social network analysis: Evolving Twitter mining

Forecasting time series by an ensemble of Artificial Neural Networks based on transforming the time series

Sequential classifiers for network intrusion detection based on data selection process

Autonomous Data Density based clustering method

Predicting Opponent Actions by Observation

Applying evolution strategies to neural networks robot controller

Sequence Classification Using Statistical Pattern Recognition

Creating User Profiles from a Command-Line Interface: A Statistical Approach

Time Series Forecasting by Evolving Artificial Neural Networks Using “Shuffle”, Cross-Validation and Ensembles

Generative Capacities of Cellular Automata Codification for Evolution of NN Codification

Modeling Consciousness for Autonomous Robot Exploration

A Comparing Method of Two Team Behaviours in the Simulation Coach Competition

Learning symbolic rules with a reactive with tags classifier system in robot navigation

Studying the Capacity of Grammatical Encoding to Generate FNN Architectures

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