Artificial Intelligence and Systems Theory: Applied to Cooperative Robots

This paper describes an approach to the design of a population of cooperative robots based on concepts borrowed from Systems Theory and Artificial Intelligence. The research has been developed under the SocRob project, carried out by the Intelligent Systems Laboratory at the Institute for Systems and Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the project stands both for "Society of Robots" and "Soccer Robots", the case study where we are testing our population of robots. Designing soccer robots is a very challenging problem, where the robots must act not only to shoot a ball towards the goal, but also to detect and avoid static (walls, stopped robots) and dynamic (moving robots) obstacles. Furthermore, they must cooperate to defeat an opposing team. Our past and current research in soccer robotics includes cooperative sensor fusion for world modeling, object recognition and tracking, robot navigation, multi-robot distributed task planning and coordination, including cooperative reinforcement learning in cooperative and adversarial environments, and behavior-based architectures for real time task execution of cooperating robot teams

Human Sexual Cycles are Driven by Culture and Match Collective Moods

It is a long-standing question whether human sexual and reproductive cycles are affected predominantly by biology or culture. The literature is mixed with respect to whether biological or cultural factors best explain the reproduction cycle phenomenon, with biological explanations dominating the argument. The biological hypothesis proposes that human reproductive cycles are an adaptation to the seasonal cycles caused by hemisphere positioning, while the cultural hypothesis proposes that conception dates vary mostly due to cultural factors, such as vacation schedule or religious holidays. However, for many countries, common records used to investigate these hypotheses are incomplete or unavailable, biasing existing analysis towards primarily Christian countries in the Northern Hemisphere. Here we show that interest in sex peaks sharply online during major cultural and religious celebrations, regardless of hemisphere location. This online interest, when shifted by nine months, corresponds to documented human birth cycles, even after adjusting for numerous factors such as language, season, and amount of free time due to holidays. We further show that mood, measured independently on Twitter, contains distinct collective emotions associated with those cultural celebrations, and these collective moods correlate with sex search volume outside of these holidays as well. Our results provide converging evidence that the cyclic sexual and reproductive behavior of human populations is mostly driven by culture and that this interest in sex is associated with specific emotions, characteristic of, but not limited to, major cultural and religious celebrations.Comment: Main Paper: 21 pages, 4 figures Supplementary Material: 66 pages, 15 figures, 13 table

¿Cómo casi destruir un mercado sin querer y no fallar en el intento? El caso del impuesto sobre los automóviles de lujo en Argentina

Under the pressure of a growing capital outflow, by the end of 2013 the Argentine government implemented what was known as the tax on "luxury cars". Even when not explicitly declared, the main objective was to reduce imports of most expensive cars to reduce the trade deficit of the automotive sector, which was contributing heavily to the capital account deficit. Even when the policy could be categorized as "successful" in terms of reducing a USD 4.5 billion deficit in 2013 to one of just over USD 0.7 billion in 2014, it had a devastating and lasting impact on the internal market, that just in 2013 had achieved a record in sales. We obtain that during the first year of the implementation of the tax, the overall impact on sales of models reached by the tax was 53.7%. Despite some differences, the negative impact took place throughout the whole year. Not surprisingly, cars reached by the highest tax rate were most affected, as well as carmakers that produce more expensive varieties. However, even when the measure may have been designed to have a direct impact on a small part of the market, the negative effects extended to the whole market.Bajo la presión de una creciente salida de capitales, a fines del año 2013 el gobierno argentino implementó lo que se conoció como el impuesto a los "autos de lujo". Aunque no declarado explícitamente, el objetivo principal era reducir las importaciones de los automóviles más caros para reducir el déficit comercial del sector automotriz, que contribuía de manera importante al déficit de la cuenta de capital. Más allá del hecho de que la política podría calificarse de "exitosa" en cuanto a la reducción de un déficit de USD 4.500 millones en 2013 a uno de poco más de USD 700 millones en 2014, tuvo un impacto devastador y duradero en el mercado interno, que apenas un año antes, en 2013, había alcanzado un récord de ventas. Los resultados muestran que durante el primer año de la aplicación del impuesto, el impacto global en las ventas de los modelos alcanzados por el mismo fue del 53,7%. A pesar de algunas diferencias, el impacto negativo se produjo a lo largo todo el año 2014. No sorprende que los automóviles alcanzados por la tasa del 50% fueran los más afectados, así como los fabricantes de modelos más caros. Sin embargo, incluso cuando la medida puede haber sido diseñada para tener un impacto directo en una pequeña parte del mercado, los efectos negativos se extendieron a la totalidad del mismo.

Comparison Between Supervised and Unsupervised Classifications of Neuronal Cell Types: A Case Study

In the study of neural circuits, it becomes essential to discern the different neuronal cell types that build the circuit. Traditionally, neuronal cell types have been classified using qualitative descriptors. More recently, several attempts have been made to classify neurons quantitatively, using unsupervised clustering methods. While useful, these algorithms do not take advantage of previous information known to the investigator, which could improve the classification task. For neocortical GABAergic interneurons, the problem to discern among different cell types is particularly difficult and better methods are needed to perform objective classifications. Here we explore the use of supervised classification algorithms to classify neurons based on their morphological features, using a database of 128 pyramidal cells and 199 interneurons from mouse neocortex. To evaluate the performance of different algorithms we used, as a “benchmark,” the test to automatically distinguish between pyramidal cells and interneurons, defining “ground truth” by the presence or absence of an apical dendrite. We compared hierarchical clustering with a battery of different supervised classification algorithms, finding that supervised classifications outperformed hierarchical clustering. In addition, the selection of subsets of distinguishing features enhanced the classification accuracy for both sets of algorithms. The analysis of selected variables indicates that dendritic features were most useful to distinguish pyramidal cells from interneurons when compared with somatic and axonal morphological variables. We conclude that supervised classification algorithms are better matched to the general problem of distinguishing neuronal cell types when some information on these cell groups, in our case being pyramidal or interneuron, is known a priori. As a spin-off of this methodological study, we provide several methods to automatically distinguish neocortical pyramidal cells from interneurons, based on their morphologies

220604

This research proposes a novel minimal-overlap centrality-driven gateway designation method for real-time wireless sensor networks (WSNs). The goal is to enhance network schedulability by design, particularly, by exploiting the relationship between path node-overlaps and gateway designation. To this aim, we define a new metric termed minimal-overlap network centrality which characterizes the overall overlapping degree between all the active flows in the network when a given node is selected as gateway. The metric is then used to designate as gateway the node which produces the least overall number of path overlaps. For the purposes of evaluation, we assume a time-synchronized channel-hopping (TSCH) WSN under centralized earliest-deadline-first (EDF) scheduling and shortest-path routing. The assessment of the WSN traffic schedulability suggests our approach is dominant over classical network centrality metrics, namely, eigenvector, closeness, betweenness, and degree. Notably, it achieves up to 50% better schedulability than a degree centrality benchmark.This work was partially supported by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology), within the CISTER Research Unit (UIDB/04234/2020); by the Operational Competitiveness Programme and Internationalization (COMPETE 2020) under the PT2020 Agreement, through the European Regional Development Fund (ERDF); also by FCT and the ESF (European Social Fund) through the Regional Operational Programme (ROP) Norte 2020, under PhD grant 2020.06685.BDN/

Soft and transferable skills acquisition through organizing a doctoral conference

UIDB/00066/2020.This article presents a 10-year experience of soft and transferable skills acquisition through the involvement of PhD students in the organization of an international conference. Soft and transferable skills acquisition is currently perceived as a core component of doctoral studies. Examples include writing and communication, teamwork, time management, leadership, resource management, negotiation, problem solving, listening, planning, entrepreneurial spirit, mastering ethics awareness, etc. The need for such skills is due to the leading role that doctoral students are expected to play in society. As such, various organizations have issued recommendations for doctoral programs to include a formal component of soft skills training. In this article, an effective way of introducing soft and transferable skills acquisition in doctoral engineering education is introduced. Namely, a form of collaborative project-based learning is designed as a compulsory course. This includes a set of base lectures, a long period of parallel working groups focusing on the various aspects of organizing an international conference, running the actual conference, and performing a post-conference assessment. Results and lessons learned demonstrate the validity and effectiveness of the proposed approach.publishersversionpublishe

230702

This article presents a novel centrality-driven gateway designation framework for the improved real-time performance of low-power wireless sensor networks (WSNs) at system design time. We target time-synchronized channel hopping (TSCH) WSNs with centralized network management and multiple gateways with the objective of enhancing traffic schedulability by design. To this aim, we propose a novel network centrality metric termed minimal-overlap centrality that characterizes the overall number of path overlaps between all the active flows in the network when a given node is selected as gateway. The metric is used as a gateway designation criterion to elect as a gateway the node leading to the minimal number of overlaps. The method is then extended to multiple gateways with the aid of the unsupervised learning method of spectral clustering. Concretely, after a given number of clusters are identified, we use the new metric at each cluster to designate as cluster gateway the node with the least overall number of overlaps. Extensive simulations with random topologies under centralized earliest-deadline-first (EDF) scheduling and shortest-path routing suggest our approach is dominant over traditional centrality metrics from social network analysis, namely, eigenvector, closeness, betweenness, and degree. Notably, our approach reduces by up to 40% the worst-case end-to-end deadline misses achieved by classical centrality-driven gateway designation methods.This work was partially supported by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology), within the CISTER Research Unit (UIDB/04234/2020); by the Operational Competitiveness Programme and Internationalization (COMPETE 2020) under the PT2020 Agreement, through the European Regional Development Fund (ERDF); also by FCT and the ESF (European Social Fund) through the Regional Operational Programme (ROP) Norte 2020, under PhD grant 2020.06685.BD.info:eu-repo/semantics/publishedVersio