Partial extinction and reinstatement

Fear extinction is not permanent but more vulnerable than the original fear memory, as relapse phenomena have traditionally shown. Partial extinction has been proposed as a strategy that may serve to mitigate relapses. Partial extinction differs from the standard procedure as it includes the occasional presentation of CS-US trials at the beginning of the extinction training. The present experiment, using an aversive differential conditioning procedure, evaluates whether partial extinction can reduce reinstatement, a specific form of relapse. The results showed that partial extinction did not mitigate reinstatement but proved effective to diminish the magnitude of the US expectation after a first reacquisition trial in a final test phase. The results reported are more consistent with theories that conceives extinction as the acquisition of new inhibitory learning rather than the erasure of the original conditioning.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Safety of permanent pacemaker implantation: a prospective study

Although pacemaker implantation is considered to be low risk, it is not exempt from complications and technical failures during the procedure, both in the short and long term, and the complications that such patients may present remain unknown. The aim has been to analyze the complication rates associated with permanent pacing and to identify if these differ between patients with or without previous antithrombotic therapy. We used a prospective, single center, observational study of 310 adult patients with indications of permanent pacing. They were hospitalized from 1 January to 31 December 2014 and followed up for 6 months after the pacemaker implant. The participants were distributed into two groups according to the antithrombotic therapy prior to the implant. The most frequent major complications were pneumothorax (3.87%) and lead dislodgement (8.39%), while superficial phlebitis (12.90%) and uncomplicated hematomas (22.58%) were presented as the most recurrent minor complications. Hematomas were the most frequent minor complication in the antithrombotic therapy cohort, and shoulder pain was reported as the most recurrent minor complication in the non-exposed group. Finding out about complications in pacemaker implants enables a complete view of the process, and hence the prioritization of actions aimed at improving safety and reducing associated risks

Financial illiteracy in Spain: a structural problem

Financial education in Spain has been traditionally a forgotten subject. Nevertheless, recent economic problems, as the economic crisis, have put into focus the lack of financial literacy that Spanish population presents. In this context, the current research intends to analyse this issue and, using the rich financial education data provided by PISA 2015 for secondary education students, study whether or not the financial education that students are receiving in Spain would be useful for their development of this competence. Our results show that financial education in Spain is in its seminal stage and that this education is not homogenously accessible by all the Spanish population. In this sense, due to its optative nature, students with low socioeconomic status and low academic achievement would auto-select into taking this education. In addition, in Spain, some modalities of financial education implementation have a negative effect, while others are not significant.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. MINECO (ECO2017-88883-P

Learning sequences of rules using classifier systems with tags

IEEE International Conference on Systems, Man, and Cybernetics. Tokyo, 12-15 October 1999.The objective of this paper was to obtain an encoding structure that would allow the genetic evolution of rules in such a manner that the number of rules and relationship in a classifier system (CS) would be learnt in the evolution process. For this purpose, an area that allows the definition of rule groups has been entered into the condition and message part of the encoded rules. This area is called internal tag. This term was coined because the system has some similarities with natural processes that take place in certain animal species, where the existence of tags allows them to communicate and recognize each other. Such CS is called a tag classifier system (TCS). The TCS has been tested in the game of draughts and compared with the classical CS. The results show an improving of the CS performance

RTCS: a reactive with tags classifier system

In this work, a new Classifier System is proposed (CS). The system, a Reactive with Tags Classifier System (RTCS), is able to take into account environmental situations in intermediate decisions. CSs are special production systems, where conditions and actions are codified in order to learn new rules by means of Genetic Algorithms (GA). The RTCS has been designed to generate sequences of actions like the traditional classifier systems, but RTCS also has the capability of chaining rules among different time instants and reacting to new environmental situations, considering the last environmental situation to take a decision. In addition to the capability to react and generate sequences of actions, the design of a new rule codification allows the evolution of groups of specialized rules. This new codification is based on the inclusion of several bits, named tags, in conditions and actions, which evolve by means of GA. RTCS has been tested in robotic navigation. Results show the suitability of this approximation to the navigation problem and the coherence of tag values in rules classification.Publicad

Applying classifier systems to learn the reactions in mobile robots

The navigation problem involves how to reach a goal avoiding obstacles in dynamic environments. This problem can be faced considering reactions and sequences of actions. Classifier systems (CSs) have proven their ability of continuous learning, however, they have some problems in reactive systems. A modified CS, namely a reactive classifier system (RCS), is proposed to overcome those problems. Two special mechanisms are included in the RCS: the non-existence of internal cycles inside the CS (no internal cycles) and the fusion of environmental message with the messages posted to the message list in the previous instant (generation list through fusion). These mechanisms allow the learning of both reactions and sequences of actions. This learning process involves two main tasks: first, discriminate between rules and, second, the discovery of new rules to obtain a successful operation in dynamic environments. DiVerent experiments have been carried out using a mini-robot Khepera to find a generalized solution. The results show the ability of the system for continuous learning and adaptation to new situations.Publicad

A reactive approach to classifier systems

IEEE International Conference on Systems, Man, and Cybernetics. San Diego, CA, 11-14 Oct. 1998The navigation problem involves how to reach a goal avoiding obstacles in dynamic environments. This problem can be faced considering reactions and/or sequences of actions. Classifier Systems (CS) have proven their ability of continuous learning, however they have some problems in reactive systems. A modified CS is proposed to overcome these problems. Two special mechanisms are included in the developed CS to allow the learning of both reactions and sequences of actions. This learning process involves two main tasks: first, discriminating between rules and second, the discovery of new rules to obtain a successful operation in dynamic environments. Different experiments have been carried out using a mini-robot Khepera to find a generalized solution. The results show the ability of the system for continuous learning and adaptation to new situations

Reactive with tags classifier system applied to real robot navigation

7th IEEE International Conference on Emerging Technologies and Factory Automation. Barcelona, 18-21 October 1999.A reactive with tags classifier system (RTCS) is a special classifier system. This system combines the execution capabilities of symbolic systems and the learning capabilities of genetic algorithms. A RTCS is able to learn symbolic rules that allow to generate sequence of actions, chaining rules among different time instants, and react to new environmental situations, considering the last environmental situation to take a decision. The capacity of RTCS to learn good rules has been prove in robotics navigation problem. Results show the suitability of this approximation to the navigation problem and the coherence of extracted rules

Knowledge acquisition including tags in a classifier system

Congress on Evolutionary Computation. Washington, DC, 6-9 July 1999.One of the major problems related to classifier systems is the loss of rules. This loss is caused by the genetic algorithm being applied on the entire population of rules jointly. Obviously, the genetic operators discriminate rules by the strength value, such that evolution favours the generation of the stronger rules. When the learning system works in an environment in which it is possible to generate a complete training set, the strength of the rules of the CS will reflect the relative relationship between rules satisfactorily and, therefore, the application of the genetic algorithm will produce the desired effects. However, when the learning process presents individual cases and allows the system to learn gradually from these cases, each learning interval with a set of individual cases can lead the strength to be distributed in favour of a given type of rules that would in turn be favoured by the genetic algorithm. Basically, the idea is to divide rules into groups such that they are forced to remain in the system. This contribution is a method of learning that allows similar knowledge to be grouped. A field in which knowledge-based systems researchers have done a lot of work is concept classification and the relationships that are established between these concepts in the stage of knowledge conceptualization for later formalization. This job of classifying and searching relationships is performed in the proposed classifier systems by means of a mechanism. Tags, that allows the classification and the relationships to be discovered without the need for expert knowledge

Robots autónomos : arquitecturas y control

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