From Individual Cognitive Maps to a Collective Cognitive Map: Prescriptive Guidelines and Measurement of Factors that Could Distort the Mapping Process

In the collective navigation scenario of a trio exploring in a foreign city, we propose a theoretical piece, which is a prescriptive guideline describing rational ways that can enable the trio to form a collective cognitive map. The guidelines center around three stages of exploration: the initial gathering of information, coming together to plan a route in the new city, and executing the exploration plan. Depending on the desires and goals of the group, they might explore together for some or all of the time, splitting up only when their individual goals diverge. The guidelines suggest an optimal plan for these different possibilities. We propose that a collective cognitive map is formed and improved during the entire cognitive navigation process as demonstrated by the trio drawing sketch maps, creating place maps, and revising other people’s place maps. However, multiple factors could distort the navigation process at various points in the proposed prescriptive guidelines. These factors include individual differences (e.g., personal navigation ability, navigation anxiety, and sex), group dynamics (e.g., leaders and followers, group strategies), and the impact of the environment (e.g., language, culture, safety, and spatiality). We describe a thought experiment for testing collective navigation, including the measurement of these factors and the corresponding possible distortions in the collective map caused by these factors. Finally, we discuss future research directions, including using virtual environments and commercial applications. By utilizing our model, people can be flexible in resolving conflicting information during goal planning while still navigating efficiently.

Modelling collective navigation via non-local communication

Collective migration occurs throughout the animal kingdom, and demands both the interpretation of navigational cues and the perception of other individuals within the group. Navigational cues orient individuals towards a destination, while it has been demonstrated that communication between individuals enhances navigation through a reduction in orientation error. We develop a mathematical model of collective navigation that synthesizes navigational cues and perception of other individuals. Crucially, this approach incorporates uncertainty inherent to cue interpretation and perception in the decision making process, which can arise due to noisy environments. We demonstrate that collective navigation is more efficient than individual navigation, provided a threshold number of other individuals are perceptible. This benefit is even more pronounced in low navigation information environments. In navigation ‘blindspots’, where no information is available, navigation is enhanced through a relay that connects individuals in information-poor regions to individuals in information-rich regions. As an expository case study, we apply our framework to minke whale migration in the northeast Atlantic Ocean, and quantify the decrease in navigation ability due to anthropogenic noise pollution.

Constructing a cohesive pattern for collective navigation based on a swarm of robotics

Swarm robotics carries out complex tasks beyond the power of simple individual robots. Limited capabilities of sensing and communication by simple mobile robots have been essential inspirations for aggregation tasks. Aggregation is crucial behavior when performing complex tasks in swarm robotics systems. Many difficulties are facing the aggregation algorithm. These difficulties are as such: this algorithm has to work under the restrictions of no information about positions, no central control, and only local information interaction among robots. This paper proposed a new aggregation algorithm. This algorithm combined with the wave algorithm to achieve collective navigation and the recruitment strategy. In this work, the aggregation algorithm consists of two main phases: the searching phase, and the surrounding phase. The execution time of the proposed algorithm was analyzed. The experimental results showed that the aggregation time in the proposed algorithm was significantly reduced by 41% compared to other algorithms in the literature. Moreover, we analyzed our results using a one-way analysis of variance. Also, our results showed that the increasing swarm size significantly improved the performance of the group.

Modelling collective navigation via nonlocal communication

Collective migration occurs throughout the animal kingdom, and demands both the interpretation of navigational cues and the perception of other individuals within the group. Navigational cues orient individuals toward a destination, while it is hypothesised that communication between individuals enhances navigation through a reduction in orientation error. We develop a mathematical model of collective navigation that synthesises navigational cues and perception of other individuals. Crucially, this approach incorporates the uncertainty inherent to cue interpretation and perception in the decision making process, which can arise due to noisy environments. We demonstrate that collective navigation is more efficient than individual navigation, provided a threshold number of other individuals are perceptible. This benefit is even more pronounced in low navigation information environments. In navigation ``blindspots'', where no information is available, navigation is enhanced through a relay that connects individuals in information-poor regions to individuals in information-rich regions. As an expository case study, we apply our framework to minke whale migration in the North East Atlantic Ocean, and quantify the decrease in navigation ability due to anthropogenic noise pollution.

Collective navigation can facilitate passage through human-made barriers by homeward migrating Pacific salmon

The mass migration of animals is one of the great wonders of the natural world. Although there are multiple benefits for individuals migrating in groups, an increasingly recognized benefit is collective navigation, whereby social interactions improve animals’ ability to find their way. Despite substantial evidence from theory and laboratory-based experiments, empirical evidence of collective navigation in nature remains sparse. Here we used a unique large-scale radiotelemetry dataset to analyse the movements of adult Pacific salmon ( Oncorhynchus sp.) in the Columbia River Basin, USA. These salmon face substantial migratory challenges approaching, entering and transiting fishways at multiple large-scale hydroelectric mainstem dams. We assess the potential role of collective navigation in overcoming these challenges and show that Chinook salmon ( O. tshawytscha ), but not sockeye salmon ( O. nerka ) locate fishways faster and pass in fewer attempts at higher densities, consistent with collective navigation. The magnitude of the density effects were comparable to major established drivers such as water temperature, and model simulations predicted that major fluctuations in population density can have substantial impacts on key quantities including mean passage time and fraction of fish with very long passage times. The magnitude of these effects indicates the importance of incorporating conspecific density and social dynamics into models of the migration process. Density effects on both ability to locate fishways and number of passage attempts have the potential to enrich our understanding of migratory energetics and success of migrating anadromous salmonids. More broadly, our work reveals a potential role of collective navigation, in at least one species, to mitigate the effects of anthropogenic barriers to animals on the move.

Ant collective cognition allows for efficient navigation through disordered environments

The cognitive abilities of biological organisms only make sense in the context of their environment. Here, we study longhorn crazy ant collective navigation skills within the context of a semi-natural, randomized environment. Mapping this biological setting into the ‘Ant-in-a-Labyrinth’ framework which studies physical transport through disordered media allows us to formulate precise links between the statistics of environmental challenges and the ants’ collective navigation abilities. We show that, in this environment, the ants use their numbers to collectively extend their sensing range. Although this extension is moderate, it nevertheless allows for extremely fast traversal times that overshadow known physical solutions to the ‘Ant-in-a-Labyrinth’ problem. To explain this large payoff, we use percolation theory and prove that whenever the labyrinth is solvable, a logarithmically small sensing range suffices for extreme speedup. Overall, our work demonstrates the potential advantages of group living and collective cognition in increasing a species’ habitable range.

The Fact and Function of Meta-Ethical Pluralism

This chapter has two objectives. The first is to argue for the fact of meta-ethical pluralism. In other words, the chapter argues that the recent empirical scholarship suggesting that people are both realists and anti-realists cannot be simply dismissed on the basis of being philosophically inadequate because even when we increase the level of clarity and rigor, the pluralism remains. The second is to argue for the function of meta-ethical pluralism. In other words, the chapter argues against the view that this pluralism in people’s meta-ethical commitments is incoherent or a sign of confusion and puts forth the view that, instead, it serves a pragmatic function—namely, that it promotes civility and aids in the individual and collective navigation of normative space within a morally imperfect world.