1,721,080 research outputs found
Learning Fuzzy Classifier Systems for Multi-Agent Coordination
No full textWe present ELF, a learning fuzzy classi®er system (LFCS), and its application to the
®eld of Learning Autonomous Agents. In particular, we will show how this kind of
Reinforcement Learning systems can be successfully applied to learn both behaviors and
their coordination for Autonomous Agents. We will discuss the importance of knowl-
edge representation approach based on fuzzy sets to reduce the search space without
losing the required precision. Moreover, we will show how we have applied ELF to
learn the distributed coordination among agents which can exchange information with
each other. The experimental validation has been done on software agents interacting in
a real-time task
Distributed design for fair coexistence in TVWS
No full textVery recently, regulatory bodies worldwide started to approve the opportunistic access of unlicensed networks to the TVWS spectrum. Hence, in the near future, multiple heterogeneous and independently-operated unlicensed networks will coexist within the same geographical area over shared TVWS. Nevertheless, the coexistence among heterogeneous unlicensed networks over TVWS represents an open problem, and innovative solutions for handling the coexistence interference are needed to fully unleash the TVWS potentials. Hence, in this paper, we design a coexistence strategy for TVWS scenarios with the following attractive features: i) fully distributed, i.e., it avoids the need of centralized interference management; ii) over-the-air communications free, i.e., it avoids the need of direct communications among the heterogeneous networks; iii) adaptive to the time- and space-dynamics of the coexistence interference; iv) selfless, i.e., it allows a fair TVWS spectrum sharing by accounting for the communication demands of each unlicensed network. These attractive features are obtained by designing a coexistence strategy based on a system of multi-dimensional ordinary differential equations, and by incorporating the tradeoff between selfish bandwidth maximization and fair spectrum allocation within the system dynamics. Performance evaluation is conducted through numerical simulations, and the results confirm the attractive features of the proposed coexistence strategy
Strong leaders don’t cheat: an evolutionary appraisal of population heterogeneity and leadership
No full textCoordination and cooperation are crucial features of many natural and artificial systems. Among the many mechanisms that have been proposed to support their emergence, leadership can play an important role. In human and other animal groups, inter-individual differences can lead to the emergence of successful leaders, who assume their role thanks to their physical or cognitive capabilities that grant them some influence over the behavior of their peers. Hence, heterogeneity in a population appears as a key element for successful leaders. Here, we present an evolutionary game theoretic model to study the effect of leadership and heterogeneity on cooperative behavior and examine the relationships between the two. We show that the presence of a leader can promote the evolution of cooperation. Moreover, we find that, when there is the possibility for a leader to emerge in the group, heterogeneity benefits cooperation. In our model, players cooperate when they are more likely to become leaders, and defect otherwise. In other words, strong leaders do not defect, but act as exemplar of prosocial behavior that, when followed, lead to full cooperation
Monitoring and Mapping of Crop Fields with UAV Swarms Based on Information Gain
Full text linkMonitoring crop fields to map features like weeds can be efficiently performed with unmanned aerial vehicles (UAVs) that can cover large areas in a short time due to their privileged perspective and motion speed. However, the need for high-resolution images for precise classification of features (e.g., detecting even the smallest weeds in the field) contrasts with the limited payload and flight time of current UAVs. Thus, it requires several flights to cover a large field uniformly. However, the assumption that the whole field must be observed with the same precision is unnecessary when features are heterogeneously distributed, like weeds appearing in patches over the field. In this case, an adaptive approach that focuses only on relevant areas can perform better, especially when multiple UAVs are employed simultaneously. Leveraging on a swarm-robotics approach, we propose a monitoring and mapping strategy that adaptively chooses the target areas based on the expected information gain, which measures the potential for uncertainty reduction due to further observations. The proposed strategy scales well with group size and leads to smaller mapping errors than optimal pre-planned monitoring approaches
Random walks in swarm robotics: An experiment with Kilobots
No full textRandom walks represent fundamental search strategies for both animal and robots, especially when there are no environmental cues that can drive motion, or when the cognitive abilities of the searching agent do not support complex localisation and mapping behaviours. In swarm robotics, random walks are basic building blocks for the individual behaviour and support the emergent collective pattern. However, there has been limited account for the correct parameterisation to be used in different search scenarios, and the relationship between search efficiency and information transfer within the swarm has been often overlooked. In this study, we analyse the efficiency of random walk patterns for a swarm of Kilobots searching a static target in two different environmental conditions entailing a bounded or an open space. We study the search efficiency and the ability to spread information within the swarm through numerical simulations and real robot experiments, and we determine what kind of random walk best fits each experimental scenario. © Springer International Publishing Switzerland 2016
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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