scholarly journals Specialization and selective social attention establishes the balance between individual and social learning

2021 ◽  
Author(s):  
Charley M. Wu ◽  
Mark K. Ho ◽  
Benjamin Kahl ◽  
Christina Leuker ◽  
Björn Meder ◽  
...  
Keyword(s):  
Social Learning ◽  
Social Interactions ◽  
Field Data ◽  
Field Of View ◽  
Game Engine ◽  
Foraging Patterns ◽  
Trade Off ◽  
Collective Foraging ◽  
Simulation Results ◽  
Spatial Trajectories

AbstractA key question individuals face in any social learning environment is when to innovate alone and when to imitate others. Previous simulation results have found that the best performing groups exhibit an intermediate balance, yet it is still largely unknown how individuals collectively negotiate this balance. We use an immersive collective foraging experiment, implemented in the Minecraft game engine, facilitating unprecedented access to spatial trajectories and visual field data. The virtual environment imposes a limited field of view, creating a natural trade-off between allocating visual attention towards individual innovation or to look towards peers for social imitation. By analyzing foraging patterns, social interactions (visual and spatial), and social influence, we shine new light on how groups collectively adapt to the fluctuating demands of the environment through specialization and selective imitation, rather than homogeneity and indiscriminate copying of others.

scholarly journals Individual exploration and selective social learning: Balancing exploration-exploitation trade-offs in collective foraging

2021 ◽  
Author(s):  
Ketika Garg ◽  
Christopher T. Kello ◽  
Paul E Smaldino
Keyword(s):  
Social Learning ◽  
Social Information ◽  
Social Cues ◽  
Optimal Combination ◽  
Trade Off ◽  
Trade Offs ◽  
Lévy Walks ◽  
Power Law Exponent ◽  
Collective Foraging ◽  
Exploration Exploitation

Search requires balancing exploring for more options and exploiting the ones previously found. Individuals foraging in a group face another trade-off: whether to engage in social learning to exploit the solutions found by others or to solitarily search for unexplored solutions. Social learning can decrease the costs of finding new resources, but excessive social learning can decrease the exploration for new solutions. We study how these two trade-offs interact to influence search efficiency in a model of collective foraging under conditions of varying resource abundance, resource density, and group size. We modeled individual search strategies as Lévy walks, where a power-law exponent (μ) controlled the trade-off between exploitative and explorative movements in individual search. We modulated the trade-off between individual search and social learning using a selectivity parameter that determined how agents responded to social cues in terms of distance and likely opportunity costs. Our results show that social learning is favored in rich and clustered environments, but also that the benefits of exploiting social information are maximized by engaging in high levels of individual exploration. We show that selective use of social information can modulate the disadvantages of excessive social learning, especially in larger groups and with limited individual exploration. Finally, we found that the optimal combination of individual exploration and social learning gave rise to trajectories with μ ≈ 2 and provide support for the general optimality such patterns in search. Our work sheds light on the interplay between individual search and social learning, and has broader implications for collective search and problem-solving.

scholarly journals Diagnostic Capabilities of a Smartphone- Based Low-Cost Microscope

2020 ◽  
Vol 6 (3) ◽  
pp. 522-525
Author(s):  
Dorina Hasselbeck ◽  
Max B. Schäfer ◽  
Kent W. Stewart ◽  
Peter P. Pott
Keyword(s):  
Low Cost ◽  
Field Of View ◽  
Parasitic Diseases ◽  
Optical Parameters ◽  
Trade Off ◽  
Resource Limited ◽  
Wide Range ◽  
Diagnostic Applications ◽  
Diagnostic Capabilities

AbstractMicroscopy enables fast and effective diagnostics. However, in resource-limited regions microscopy is not accessible to everyone. Smartphone-based low-cost microscopes could be a powerful tool for diagnostic and educational purposes. In this paper, the imaging quality of a smartphone-based microscope with four different optical parameters is presented and a systematic overview of the resulting diagnostic applications is given. With the chosen configuration, aiming for a reasonable trade-off, an average resolution of 1.23 μm and a field of view of 1.12 mm2 was achieved. This enables a wide range of diagnostic applications such as the diagnosis of Malaria and other parasitic diseases.

A university sport coach community of practice: Using a value creation framework to explore learning and social interactions

2017 ◽  
Vol 12 (3) ◽  
pp. 287-302 ◽  
Author(s):  
Rachael Bertram ◽  
Diane M Culver ◽  
Wade Gilbert
Keyword(s):  
Social Learning ◽  
Social Interactions ◽  
Community Of Practice ◽  
Value Creation ◽  
National Collegiate Athletic Association ◽  
A Value ◽  
Coaching Strategies ◽  
Division 1 ◽  
Practice Approach ◽  
University Setting

Coaches often identify social learning situations as the most valuable and influential to their learning. Thus, researchers have proposed implementing social learning initiatives, in particular, the community of practice approach. The purpose of the present study was to explore how an existing coach community of practice was created and sustained in a university setting, and to assess what value was created by participating in the community of practice. Participants included four National Collegiate Athletic Association Division 1 coaches from a university in the Southwestern United States. Data collection included an individual interview with each coach. Interviews were analysed using a value creation framework. The findings revealed that the coaches created value within all five cycles of Wenger et al.’s framework. In particular, the coaches learned a number of coaching strategies, some of which they were able to implement, and as a result, observe benefits in their coaching and athletes’ performance.

scholarly journals Task allocation and site fidelity jointly influence foraging regulation in honeybee colonies

2017 ◽  
Vol 4 (8) ◽  
pp. 170344 ◽  
Author(s):  
Thiago Mosqueiro ◽  
Chelsea Cook ◽  
Ramon Huerta ◽  
Jürgen Gadau ◽  
Brian Smith ◽  
...  
Keyword(s):  
Site Fidelity ◽  
Collective Behaviour ◽  
Trade Off ◽  
Agent Based ◽  
Resource Collection ◽  
Group Members ◽  
Collective Foraging ◽  
The Individual ◽  
Colony Level ◽  
And Task

Variation in behaviour among group members often impacts collective outcomes. Individuals may vary both in the task that they perform and in the persistence with which they perform each task. Although both the distribution of individuals among tasks and differences among individuals in behavioural persistence can each impact collective behaviour, we do not know if and how they jointly affect collective outcomes. Here, we use a detailed computational model to examine the joint impact of colony-level distribution among tasks and behavioural persistence of individuals, specifically their fidelity to particular resource sites, on the collective trade-off between exploring for new resources and exploiting familiar ones. We developed an agent-based model of foraging honeybees, parametrized by data from five colonies, in which we simulated scouts, who search the environment for new resources, and individuals who are recruited by the scouts to the newly found resources, i.e. recruits. We varied the persistence of returning to a particular food source of both scouts and recruits and found that, for each value of persistence, there is a different optimal ratio of scouts to recruits that maximizes resource collection by the colony. Furthermore, changes to the persistence of scouts induced opposite effects from changes to the persistence of recruits on the collective foraging of the colony. The proportion of scouts that resulted in the most resources collected by the colony decreased as the persistence of recruits increased. However, this optimal proportion of scouts increased as the persistence of scouts increased. Thus, behavioural persistence and task participation can interact to impact a colony's collective behaviour in orthogonal directions. Our work provides new insights and generates new hypotheses into how variations in behaviour at both the individual and colony levels jointly impact the trade-off between exploring for new resources and exploiting familiar ones.

scholarly journals Critical density for coverage and connectivity in non-orientation directional sensor network

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092575
Author(s):  
Lin Kang ◽  
Zengshou Dong ◽  
Yanjie Qi
Keyword(s):  
Sensor Network ◽  
Critical Density ◽  
Region Of Interest ◽  
Field Of View ◽  
Wireless Sensor ◽  
Connected Component ◽  
Simulation Results ◽  
Coverage And Connectivity ◽  
Directional Sensor Network ◽  
Directional Sensor

Both coverage and connectivity are important problems in wireless sensor networks. As more and more non-orientation sensors are continuously added into the region of interest, the size of covered component and connected component increases; at some point, the network can achieve an entire coverage and full connectivity after which the network percolates. In this article, we analyze the critical density in non-orientation directional sensor network in which the orientations of the sensors are random and the sensors are deployed according to the Poisson point process. We propose an approach to compute the critical density in such a network. A collaborating path is proposed with the sum of field-of-view angles of two collaborating sensors being π. Then a correlated model of non-orientation directional sensing sectors for percolation is proposed to solve the coverage and connectivity problems together. The numerical simulations confirm that percolation occurs on the estimated critical densities. It is worth mentioning that the theoretical analysis and simulation results give insights into the design of directional sensor network in practice.

scholarly journals Individual learning phenotypes drive collective behavior

2020 ◽  
Vol 117 (30) ◽  
pp. 17949-17956 ◽  
Author(s):  
Chelsea N. Cook ◽  
Natalie J. Lemanski ◽  
Thiago Mosqueiro ◽  
Cahit Ozturk ◽  
Jürgen Gadau ◽  
...  
Keyword(s):  
Individual Differences ◽  
Social Interactions ◽  
Cognitive Ability ◽  
Honey Bee ◽  
Collective Behavior ◽  
Cognitive Abilities ◽  
Learning Behavior ◽  
Collective Foraging ◽  
Familiar Stimuli ◽  
Bee Colonies

Individual differences in learning can influence how animals respond to and communicate about their environment, which may nonlinearly shape how a social group accomplishes a collective task. There are few empirical examples of how differences in collective dynamics emerge from variation among individuals in cognition. Here, we use a naturally variable and heritable learning behavior called latent inhibition (LI) to show that interactions among individuals that differ in this cognitive ability drive collective foraging behavior in honey bee colonies. We artificially selected two distinct phenotypes: high-LI bees that ignore previously familiar stimuli in favor of novel ones and low-LI bees that learn familiar and novel stimuli equally well. We then provided colonies differentially composed of different ratios of these phenotypes with a choice between familiar and novel feeders. Colonies of predominantly high-LI individuals preferred to visit familiar food locations, while low-LI colonies visited novel and familiar food locations equally. Interestingly, in colonies of mixed learning phenotypes, the low-LI individuals showed a preference to visiting familiar feeders, which contrasts with their behavior when in a uniform low-LI group. We show that the shift in feeder preference of low-LI bees is driven by foragers of the high-LI phenotype dancing more intensely and attracting more followers. Our results reveal that cognitive abilities of individuals and their social interactions, which we argue relate to differences in attention, drive emergent collective outcomes.

scholarly journals A Data Transmission Algorithm Based on Dynamic Grid Division for Coal Goaf Temperature Monitoring

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Qingsong Hu ◽  
Lixin Wu ◽  
Fei Geng ◽  
Can Cao
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Data Transmission ◽  
Field Data ◽  
Temperature Monitoring ◽  
Wireless Sensor ◽  
Dynamic Features ◽  
Transmission Scheme ◽  
Simulation Results ◽  
Grid Division

WSN (wireless sensor network) is a perfect tool of temperature monitoring in coal goaf. Based on the three-zone theory of goaf, the GtmWSN model is proposed, and its dynamic features are analyzed. Accordingly, a data transmission scheme, named DTDGD, is worked out. Firstly, sink nodes conduct dynamic grid division on the GtmWSN according to virtual semicircle. Secondly, each node will confirm to which grid it belongs based on grid number. Finally, data will be delivered to sink nodes with greedy forward and hole avoidance. Simulation results and field data showed that the GtmWSN and DTDGD satisfied the lifetime need of goaf temperature monitoring.

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