scholarly journals A model of collective behavior based purely on vision

2019 ◽  
Author(s):  
Renaud Bastien ◽  
Pawel Romanczuk
Keyword(s):  
Collective Behavior ◽  
Spatial Representation ◽  
External Information ◽  
Central Feature ◽  
Mathematical Framework ◽  
Systems Neuroscience ◽  
Novel Approach ◽  
Classical Models ◽  
Explanatory Success ◽  
The Individual

Classical models of collective behavior often take a “birds-eye perspective,” assuming that individuals have access to social information that is not directly available (e.g., the behavior of individuals outside of their field of view). Despite the explanatory success of those models, it is now thought that a better understanding needs to incorporate of the perception of the individual, i.e. how internal and external information are acquired and processed. In particular, vision has appeared to be a central feature to gather external information and influence the collective organization of the group. Here we show that a vision based model of collective behavior is sufficient to generate organized collective behavior in the absence of spatial representation and collision. Our work suggests a novel approach for development of purely vision-based autonomous swarm robotic systems, and formulates a mathematical framework for exploration of perception-based interactions and how they differ from physical ones. Thus, it is of broader relevance for self-organization in complex systems, neuroscience, behavioral sciences and engineering.

scholarly journals A model of collective behavior based purely on vision

2020 ◽  
Vol 6 (6) ◽  
pp. eaay0792
Author(s):  
Renaud Bastien ◽  
Pawel Romanczuk
Keyword(s):  
Collective Behavior ◽  
Spatial Representation ◽  
Field Of View ◽  
Robotic Systems ◽  
External Information ◽  
Central Feature ◽  
Mathematical Framework ◽  
Classical Models ◽  
Explanatory Success ◽  
The Individual

Classical models of collective behavior often take a “bird’s-eye perspective,” assuming that individuals have access to social information that is not directly available (e.g., the behavior of individuals outside of their field of view). Despite the explanatory success of those models, it is now thought that a better understanding needs to incorporate the perception of the individual, i.e., how internal and external information are acquired and processed. In particular, vision has appeared to be a central feature to gather external information and influence the collective organization of the group. Here, we show that a vision-based model of collective behavior is sufficient to generate organized collective behavior in the absence of spatial representation and collision. Our work suggests a different approach for the development of purely vision-based autonomous swarm robotic systems and formulates a mathematical framework for exploration of perception-based interactions and how they differ from physical ones.

scholarly journals Predictive Control of Aerial Swarms in Cluttered Environments

2020 ◽  
Author(s):  
Enrica Soria ◽  
Fabrizio Schiano ◽  
Dario Floreano
Keyword(s):  
Real World ◽  
Urban Areas ◽  
Collective Motion ◽  
Tight Coupling ◽  
Cluttered Environments ◽  
Individual Level ◽  
Robotic Swarms ◽  
Classical Models ◽  
Explanatory Success ◽  
The Individual

Abstract Classical models of aerial swarms often describe global coordinated motion as the combination of local interactions that happen at the individual level. Mathematically, these interactions are represented with Potential Fields. Despite their explanatory success, these models fail to guarantee rapid and safe collective motion when applied to aerial robotic swarms flying in cluttered environments of the real world, such as forests and urban areas. Moreover, these models necessitate a tight coupling with the deployment scenarios to induce consistent swarm behaviors. Here, we propose a predictive model that combines the local principles of potential field models with the knowledge of the agents’ dynamics. We show that our approach improves the speed, order, and safety of the swarm, it is independent of the environment layout, and scalable in the swarm speed and inter-agent distance. Our model is validated with a swarm of five quadrotors that can successfully navigate in a real-world indoor environment populated with obstacles.

scholarly journals Material Geometry of Binary Composites

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 892
Author(s):  
Marcelo Epstein
Keyword(s):  
Continuum Mechanics ◽  
Mathematical Framework ◽  
Double Groupoid ◽  
The Individual ◽  
Elastic Composites

The constitutive characterization of the uniformity and homogeneity of binary elastic composites is presented in terms of a combination of the material groupoids of the individual constituents. The incorporation of these two groupoids within a single double groupoid is proposed as a viable mathematical framework for a unified formulation of this and similar kinds of problems in continuum mechanics.

Using hidden Markov models to find discrete targets in continuous sociophonetic data

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Daniel Duncan
Keyword(s):  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov ◽  
Abstract Representation ◽  
Language Variation And Change ◽  
Novel Approach ◽  
Single Target ◽  
The Individual ◽  
Individual Speaker

Abstract Advances in sociophonetic research resulted in features once sorted into discrete bins now being measured continuously. This has implied a shift in what sociolinguists view as the abstract representation of the sociolinguistic variable. When measured discretely, variation is variation in selection: one variant is selected for production, and factors influencing language variation and change are influencing the frequency at which variants are selected. Measured continuously, variation is variation in execution: speakers have a single target for production, which they approximate with varying success. This paper suggests that both approaches can and should be considered in sociophonetic analysis. To that end, I offer the use of hidden Markov models (HMMs) as a novel approach to find speakers’ multiple targets within continuous data. Using the lot vowel among whites in Greater St. Louis as a case study, I compare 2-state and 1-state HMMs constructed at the individual speaker level. Ten of fifty-two speakers’ production is shown to involve the regular use of distinct fronted and backed variants of the vowel. This finding illustrates HMMs’ capacity to allow us to consider variation as both variant selection and execution, making them a useful tool in the analysis of sociophonetic data.

scholarly journals HPM: A Hybrid Model for User’s Behavior Prediction Based on N-Gram Parsing and Access Logs

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Sonia Setia ◽  
Verma Jyoti ◽  
Neelam Duhan
Keyword(s):  
Web Mining ◽  
Contextual Information ◽  
Hybrid Approach ◽  
Web Pages ◽  
Continuous Growth ◽  
Novel Approach ◽  
Content Mining ◽  
Long Access ◽  
N Gram ◽  
The Individual

The continuous growth of the World Wide Web has led to the problem of long access delays. To reduce this delay, prefetching techniques have been used to predict the users’ browsing behavior to fetch the web pages before the user explicitly demands that web page. To make near accurate predictions for users’ search behavior is a complex task faced by researchers for many years. For this, various web mining techniques have been used. However, it is observed that either of the methods has its own set of drawbacks. In this paper, a novel approach has been proposed to make a hybrid prediction model that integrates usage mining and content mining techniques to tackle the individual challenges of both these approaches. The proposed method uses N-gram parsing along with the click count of the queries to capture more contextual information as an effort to improve the prediction of web pages. Evaluation of the proposed hybrid approach has been done by using AOL search logs, which shows a 26% increase in precision of prediction and a 10% increase in hit ratio on average as compared to other mining techniques.

Dynamics and Bifurcations in Networks Designed for Frequency Conversion

2021 ◽  
Vol 31 (12) ◽  
pp. 2130037
Author(s):  
Visarath In ◽  
Antonio Palacios
Keyword(s):  
Collective Behavior ◽  
Frequency Conversion ◽  
Signal Frequency ◽  
Complex Signals ◽  
Multiple Frequencies ◽  
Basic Ideas ◽  
The Individual ◽  
Parallel Arrays ◽  
To Receive ◽  
Down Conversion

This article reviews recent progress in signal frequency up-conversion and down-conversion, both theory and experiments with network implementations. The fundamental idea is to exploit the inherent symmetry of networks to produce collective behavior in which certain oscillators tend to oscillate at different frequencies. This concept is significantly different from other techniques, e.g. master-slave systems, in the sense that the collective behavior arises naturally from the mutual interactions of the individual units, and without any external forcing. In this manuscript, we present a comprehensive review of the basic ideas, methods, and experiments of the symmetry-based phenomenon of frequency conversion. In addition, we present a review of a device implementation of a broad spectrum analyzer, which motivated the development of systematic methods to up- and down-convert frequencies of oscillations. This device is made up of large parallel arrays of analog nonlinear oscillators with the ability to receive complex signals containing multiple frequencies and instantaneously lock-on or respond to a received signal in a few oscillation cycles.

scholarly journals A Genetic Algorithm Approach for Group Recommender System Based on Partial Rankings

2018 ◽  
Vol 29 (1) ◽  
pp. 653-663 ◽  
Author(s):  
Ritu Meena ◽  
Kamal K. Bharadwaj
Keyword(s):  
Genetic Algorithm ◽  
Recommender Systems ◽  
Rank Aggregation ◽  
Partial Ranking ◽  
Novel Approach ◽  
Kendall Tau Distance ◽  
Ultimate Objective ◽  
Aggregation Technique ◽  
The Individual ◽  
Group Recommender

Abstract Many recommender systems frequently make suggestions for group consumable items to the individual users. There has been much work done in group recommender systems (GRSs) with full ranking, but partial ranking (PR) where items are partially ranked still remains a challenge. The ultimate objective of this work is to propose rank aggregation technique for effectively handling the PR problem. Additionally, in real applications, most of the studies have focused on PR without ties (PRWOT). However, the rankings may have ties where some items are placed in the same position, but where some items are partially ranked to be aggregated may not be permutations. In this work, in order to handle problem of PR in GRS for PRWOT and PR with ties (PRWT), we propose a novel approach to GRS based on genetic algorithm (GA) where for PRWOT Spearman foot rule distance and for PRWT Kendall tau distance with bucket order are used as fitness functions. Experimental results are presented that clearly demonstrate that our proposed GRS based on GA for PRWOT (GRS-GA-PRWOT) and PRWT (GRS-GA-PRWT) outperforms well-known baseline GRS techniques.

Foundation for Model Integration: Semantic Backplane

2012 ◽  
Author(s):  
Gabor Simko ◽  
Tihamer Levendovszky ◽  
Sandeep Neema ◽  
Ethan Jackson ◽  
Ted Bapty ◽  
...  
Keyword(s):  
Design Flow ◽  
Model Transformations ◽  
Model Integration ◽  
Mathematical Framework ◽  
Modeling Languages ◽  
Tool Chain ◽  
Model Based ◽  
Essential Properties ◽  
The Individual ◽  
Term Algebra

One of the primary goals of the Adaptive Vehicle Make (AVM) program of DARPA is the construction of a model-based design flow and tool chain, META, that will provide significant productivity increase in the development of complex cyber-physical systems. In model-based design, modeling languages and their underlying semantics play fundamental role in achieving compositionality. A significant challenge in the META design flow is the heterogeneity of the design space. This challenge is compounded by the need for rapidly evolving the design flow and the suite of modeling languages supporting it. Heterogeneity of models and modeling languages is addressed by the development of a model integration language – CyPhy – supporting constructs needed for modeling the interactions among different modeling domains. CyPhy targets simplicity: only those abstractions are imported from the individual modeling domains to CyPhy that are required for expressing relationships across sub-domains. This “semantic interface” between CyPhy and the modeling domains is formally defined, evolved as needed and verified for essential properties (such as well-formedness and invariance). Due to the need for rapid evolvability, defining semantics for CyPhy is not a “one-shot” activity; updates, revisions and extensions are ongoing and their correctness has significant implications on the overall consistency of the META tool chain. The focus of this paper is the methods and tools used for this purpose: the META Semantic Backplane. The Semantic Backplane is based on a mathematical framework provided by term algebra and logics, incorporates a tool suite for specifying, validating and using formal structural and behavioral semantics of modeling languages, and includes a library of metamodels and specifications of model transformations.

Self Configuration of a Novel Miniature Ultrasonic Linear Motor

2006 ◽  
Vol 113 ◽  
pp. 167-172
Author(s):  
Maik Mracek ◽  
Tobias Hemsel ◽  
Piotr Vasiljev ◽  
Jörg Wallaschek
Keyword(s):  
High Power ◽  
Collective Behavior ◽  
Industrial Application ◽  
Limited Range ◽  
Linear Superposition ◽  
Ultrasonic Motors ◽  
Higher Power ◽  
Small Force ◽  
The Individual ◽  
Individual Motor

Rotary ultrasonic motors have found broad industrial application in camera lens drives and other systems. Linear ultrasonic motors in contrast have only found limited applications. The main reason for the limited range of application of these very attractive devices seems to be their small force and power range. Attempts to build linear ultrasonic motors for high forces and high power applications have not been truly successful yet. To achieve drives, larger force and higher power, and multiple miniaturized motors can be combined. This approach, however, is not as simple as it appears at first glance. The electromechanical behavior of individual motors differs slightly due to manufacturing and assembly tolerances. Individual motor characteristics are strongly dependent on the driving parameters (frequency, voltage, temperature, pre-stress, etc.) and the driven load and the collective behavior of the swarm of motors is not just the linear superposition of the individual drive’s forces.

Teacher’s Corner: Toward a Coherent View of Reliability in Test Theory

1997 ◽  
Vol 22 (4) ◽  
pp. 478-484
Author(s):  
Heng Li ◽  
Howard Wainer
Keyword(s):  
Internal Consistency ◽  
Test Scores ◽  
General Framework ◽  
Test Theory ◽  
Mathematical Framework ◽  
Individual Character ◽  
The Individual ◽  
Reliability Coefficients

Reliability of test scores, as estimated through measures of internal consistency, has been characterized mathematically in many ways that appear, on the surface at least, to be very dissimilar to one another. In this essay we provide a general mathematical framework that specializes to four different reliability coefficients. Through consideration of this general framework it becomes easier to convey to students both the individual character of the different formulations of reliability and the extent of their underlying similarity. In addition to providing a coherent view of reliability, the unified formula is also found to be a convenient vehicle for introducing more specialized topics, such as the Kaiser-Guttman rule.

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