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Ravid Cohen

Publications and source records attributed to Ravid Cohen.

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Sensory Regimes of Effective Distributed Searching without Leaders

Collective animal movement fascinates children and scientists alike. One of the most commonly given explanations for collective animal movement is improved foraging. Animals are hypothesized to gain from searching for food in groups. Here, we use a computer simulation to analyze how moving in a group assists searching for food. We use a well-established collective movement model that only assumes local interactions between individuals without any leadership, in order to examine the benefits of group searching. We focus on how the sensory abilities of the simulated individuals, and specifically their ability to detect food and to follow neighbours, influence searching dynamics and searching performance. We show that local interactions between neighbors are sufficient for the formation of groups, which search more efficiently than independently moving individuals. Once a member of a group finds food, this information diffuses through the group and results in a convergence of up to 85\% of group members on the food. Interestingly, this convergence behavior can emerge from the local interactions between group members without a need to explicitly define it. In order to understand the principles underlying the group's performance, we perturb many of the model's basic parameters, including its social, environmental and sensory parameters. We test a wide range of biological-plausible sensory regimes, relevant to different species and different sensory modalities and examine how they effect group-foraging performance. This thorough analysis of model parameters allows for the generalization of our results to a wide range of organisms, which rely on different sensory modalities, explaining why they move and forage in groups.

cs.MA

Maintaining the Union of Unit Discs under Insertions with Near-Optimal Overhead

We present efficient dynamic data structures for maintaining the union of unit discs and the lower envelope of pseudo-lines in the plane. More precisely, we present three main results in this paper: (i) We present a linear-size data structure to maintain the union of a set of unit discs under insertions. It can insert a disc and update the union in $O((k+1) \log^2 n)$ time, where $n$ is the current number of unit discs and $k$ is the combinatorial complexity of the structural change in the union due to the insertion of the new disc. It can also compute, within the same time bound, the area of the union after the insertion of each disc. (ii) We propose a linear-size data structure for maintaining the lower envelope of a set of $x$-monotone pseudo-lines. It can handle insertion/deletion of a pseudo-line in $O(\log^2 n)$ time; for a query point $x_0\in\mathbb{R}$, it can report, in $O(\log n)$ time, the point on the lower envelope with $x$-coordinate $x_0$; and for a query point $q\in\mathbb{R}^2$, it can return all $k$ pseudo-lines lying below $q$ in time $O(\log n+k\log^2 n)$. (iii) We present a linear-size data structure for storing a set of circular arcs of unit radius (not necessarily on the boundary of the union of the corresponding discs), so that for a query unit disc $D$, all input arcs intersecting $D$ can be reported in $O(n^{1/2+\varepsilon} + k)$ time, where $k$ is the output size and $\varepsilon > 0$ is an arbitrarily small constant. A unit-circle arc can be inserted or deleted in $O(\log^2 n)$ time.

cs.CG

Dynamic Maintenance of the Lower Envelope of Pseudo-Lines

We present a fully dynamic data structure for the maintenance of lower envelopes of pseudo-lines. The structure has $O(\log^2 n)$ update time and $O(\log n)$ vertical ray shooting query time. To achieve this performance, we devise a new algorithm for finding the intersection between two lower envelopes of pseudo-lines in $O(\log n)$ time, using \emph{tentative} binary search; the lower envelopes are special in that at $x=-\infty$ any pseudo-line contributing to the first envelope lies below every pseudo-line contributing to the second envelope. The structure requires $O(n)$ storage space.

cs.CG