Naïve individuals promote collective exploration in homing pigeons

Group-living animals that rely on stable foraging or migratory routes can develop behavioural traditions to pass route information down to inexperienced individuals. Striking a balance between exploitation of social information and exploration for better alternatives is essential to prevent the spread of maladaptive traditions. We investigated this balance during cumulative route development in the homing pigeon Columba livia. We quantified information transfer within pairs of birds in a transmission-chain experiment and determined how birds with different levels of experience contributed to the exploration–exploitation trade-off. Newly introduced naïve individuals were initially more likely to initiate exploration than experienced birds, but the pair soon settled into a pattern of alternating leadership with both birds contributing equally. Experimental pairs showed an oscillating pattern of exploration over generations that might facilitate the discovery of more efficient routes. Our results introduce a new perspective on the roles of leadership and information pooling in the context of collective learning.

Mapping Autistic Wayfinding in Urban Environments

Needs and preferences in wayfinding tasks of people with autism spectrum disorders (ASD) have been a topic of ongoing discussion in the scientific literature over the last decades. While different tasks have revealed both autistic strengths (e.g., encoding and recall of route information) and weaknesses (e.g., understanding allocentric representations), ASD spatial behaviour is not fully understood yet. In this paper we focus on spatial uncertainty, which is the discrepancy between a-priori expectation and in-situ experience and thus a constant factor in ASD wayfinding tasks. As a matter of course, spatial uncertainty is inevitable, always resulting from a dynamic interaction of situational qualities (e.g., noise or smell). Nevertheless, mapping uncertainty and the underlying spatial patterns in an organized way might help users from the ASD spectrum to better prepare for the different levels of expectable uncertainty in route. We propose a framework of conceptualizing, measuring, and mapping spatial uncertainty from an autistic viewpoint. The discussion of this framework is based on a qualitative analysis of the spatial behaviour of B, a five-year-old child with ASD and nonverbal communication, in an urban environment. We compare the level of spatial uncertainty of the routes developed by B against the routes indicated by ourselves.

Statistical Guarantee of Timeliness in Networks of IoT Devices

The Internet of Things (IoT) paradigm, has opened up the possibility of using the ubiquity of small devices to route information without the necessity of being connected to a Wide Area Network (WAN). Use cases of IoT devices sending updates that are routed and delivered by other IoT devices have been proposed in the literature. In this paper we focus on receivers only interested in the freshest updates from the sending device. In particular, the dynamic network created by routing/gossiping through small devices creates the possibility of delivering updates out of order. Thus, the entire process can be studied well through a queueing system with infinitely many servers, all serving updates with a random service time. Age of Information (AoI) was proposed as the main metric to measure information freshness. We study the amount of time that the AoI is over a certain threshold at the receiver end as a Quality of Service (QoS) measure, called update outage probability. Particularly, given the recent interest in the literature for time domain analysis of the AoI, we obtain the exact expressions for the AoI, peak AoI (pAoI), effective service time and effective departure time distributions for an M/M/$\infty$ queuing system from a time domain perspective, and study the interdependence between the various parameters involved in order to satisfy a given statistical constraint on timeliness.

Analysis on route information failure in IP core networks by NFV-based test environment

Stable and high-quality Internet connectivity is mandatory for 5G mobile networks. However, the pandemic of COVID-19 has forced global and large-scale staying at home and telecommuting in many countries. The increasing traffic has induced more pressure on networks, devices and cloud data centers. It becomes an essential task for network operators to enable their ability to automatically and rapidly detect network and device failures. We propose a highly practical method based on highly practical technology. Our method has a high generalization ability that can efficiently extract features from large-scale unstructured data and ensure high accuracy prediction. First, 997 useful features are extracted from 28GB-per-day network logs. Then, a differential approach is employed to preprocess the extracted features so as to highlight the differences between normal and abnormal states. Third, those features are refined based on the feature importance we calculated. According to our experiment, the proposed feature extraction and refinement method can reduce computation without degrading the performance. Among the five types of failures, we achieve a 100% recall rate in four types and the rest can also reach 71%. Overall, the total average prediction accuracy of the proposed method is 94%.

Effect of Compositions of MRT System Route Maps on Cognitive Mapping

Route maps, common in public transportation systems, refer to thematic maps drawn according to topological concepts. To simplify complex route information, a transport network is represented using primary graphic elements. First used in 1931 with topological concepts, the octilinear design has influenced the compositions of traffic route maps to this day. The current study involved cognitive mapping research on a representative route map in Taiwan: the Metro Taipei Route Map. Through two task experiments, this study analyzed users’ cognitive behavior when using the route map and alternative route map representations. The results indicated that the route map composed of all curves resulted in higher user performance than maps using a hybrid system and the conventional octilinear system. The route map based on the hybrid system, which included a route in the shape of a perfect circle, was highly evaluated and subjectively preferred by the users. Thus, the addition of appropriate curves in route maps is beneficial for improving usability, cognitive memory, and subjective evaluation. Finally, adding travel time information to a route map effectively enhances users’ decision-making during route planning.

Naïve individuals promote collective exploration in homing pigeons

Group-living animals that rely on stable foraging or migratory routes can develop behavioural traditions to pass route information down to inexperienced individuals. Striking a balance between exploitation of social information and exploration for better alternatives is essential to prevent the spread of maladaptive traditions. We investigated this balance during cumulative route development in the homing pigeon Columba livia. We quantified causal interactions within pairs of birds in a transmission-chain experiment and determined how birds with different levels of experience contributed to the exploration–exploitation trade-off. Newly introduced naïve individuals were initially more likely to initiate exploration than experienced birds, but the pair soon settled into a pattern of alternating leadership with both birds contributing equally. Experimental pairs showed an oscillating pattern of exploration over generations that might facilitate the discovery of more efficient routes. Our results introduce a new perspective on the roles of leadership and information pooling in the context of collective learning.

Analisis Perbandingan Algoritma Djikstra, A-Star, dan Floyd Warshall dalam Pencarian Rute Terdekat pada Objek Wisata Kabupaten Dompu

<p>Diera industri 4.0, penggunaan peta tidak lagi berbentuk lembaran ataupun buku. Kini terdapat sebuah layananan peta digital yaitu <em>platform</em> Leafleat.js, yang memudahkan penggunanya untuk mendapatkan informasi rute dari objek ke objek lainnya dan mencari lokasi hampir diseluruh dunia. Pada penelitian ini menggunakan objek yang <em>real </em>yaitu menampilkan lokasi sebenarnya menggunakan <em>platform</em> Leaflet.js dan parameter yang berbeda, dari hal tersebut penelitian ini akan membandingkan kinerja dari Algoritma <em>Dijkstra</em>, A* dan <em>Floyd Warshall</em> untuk menentukan waktu proses pencarian rute terdekat dari objek wisata ke objek wisata lain menggunakan bahasa pemograman PHP. Hasil pengujian program didapatkan jarak dan rute yang sama serta rata-rata waktu proses program yang berbeda. Waktu proses algoritma <em>Dijkstra</em> sebesar 0,0060 detik, algoritma A* sebesar 0,0067 dan algoritma <em>Floyd Warshall</em> sebesar 0,0433 detik. Berdasarkan hasil tersebut bahwa algoritma <em>Dijkstra</em> lebih unggul dalam proses pencarian rute.</p><p> </p><p><em><strong>Abstract</strong></em></p><p><em>In the industrial era 4.0, the use of maps is no longer made of book sheets. Now a digital map service is available, the Leafleat.js platform, which provides users to get route information from other attractions and find locations that have been saved by the world. In this study using real objects that display the actual location using the Leaflet.js platform and different parameters, from this study will compare the performance of the Dijkstra, A * and Floyd Warshall Algorithms for the process of finding other tourist information using the PHP programming language. The results of testing the program obtained the same distance and route with different program processing time. Dijkstra algorithm processing time is 0.0060 seconds, A* algorithm is 0.0067 and Floyd Warshall algorithm is 0.0433 seconds. Based on these results, Dijkstra is superior in the route search process.</em></p><p><em><strong><br /></strong></em></p>

Congratulations! Journal of Robotics and Mechatronics Best Paper Award 2020

Navigation Based on Metric Route Information in Places Where the Mobile Robot Visits for the First Time We are pleased to announce that the 13th Journal of Robotics and Mechatronics Best Paper Award (JRM Best Paper Award 2020) has been decided by the JRM editorial committee. The following paper won the JRM Best Paper Award 2020, severely selected from among all 77 papers published in Vol.31 (2019). The Best Paper Award ceremony was held in Gakushi-Kaikan, Tokyo, Japan, on December 23, 2020 (both on-site and online), attended by the authors and JRM editorial committee members who took part in the selection process. The award winner will also be announced on the JRM website and was given a certificate and a nearly US$1,000 honorarium. We congratulate the winners and sincerely wish them success in the future. Asahi Handa, Azumi Suzuki, Hisashi Date, Ryohsuke Mitsudome, Takashi Tsubouchi, and Akihisa Ohya J. Robot. Mechatron., Vol.31, No.2, pp. 180-193, April 2019 doi: 10.20965/jrm.2019.p0180

Informational Cost and Networks Navigability

Understanding how information navigates through nodes of a complex network has become an increasingly pressing problem across scientific disciplines. Several approaches have been proposed on the basis of shortest paths or diffusive navigation. However, no existing approaches have tackled the challenges of efficient communication in networks without full knowledge of their global topology under external noise. Here, we develop a first principles approach and mathematical formalism to determine the informational cost of navigating a network under different levels of external noise. Using this approach we discover the existence of a trade-off between the ways in which networks route information through shortest paths, their entropies and stability, which define three classes of real-world networks. This approach reveals that environmental pressure has shaped the ways in which information is transferred in bacterial metabolic net-works and allowed us to determine the levels of noise at which a protein-protein interaction network seems to work in normal conditions in a cell.