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20062026
most citedIndividual versus collective cognition in social insects

110 citations · 483 across the 37 of their papers we have counts for

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Showing cs.DSShow all

9 papers · 1 filter

cs.DS2026

Intermittent Cauchy walks enable optimal 3D search across target shapes and sizes

Matteo Stromieri, Emanuele Natale, Amos Korman

Efficiently locating rare targets requires balancing the exploration of novel space with the exploitation of local vicinities. While this tradeoff is well-documented in simplified…

cs.DS2020★ 1 cited

Exploitation of Multiple Replenishing Resources with Uncertainty

Amos Korman, Yuval Emek, Simon Collet +2

We consider an optimization problem in which a (single) bat aims to exploit the nectar in a set of cacti with the objective of maximizing the expected total amount of nectar it…

cs.DS2020★ 42 cited

Intermittent Inverse-Square Lévy Walks are Optimal for Finding Targets of All Sizes

Brieuc Guinard, Amos Korman

Lévy walks are random walk processes whose step-lengths follow a long-tailed power-law distribution. Due to their abundance as movement patterns of biological organisms, significan…

cs.DS2016★ 5 cited

An Optimal Ancestry Labeling Scheme with Applications to XML Trees and Universal Posets

Pierre Fraigniaud, Amos Korman

In this paper we solve the ancestry-labeling scheme problem which aims at assigning the shortest possible labels (bit strings) to nodes of rooted trees, so that ancestry queries be…

cs.DS2016★ 2 cited

Searching Trees with Permanently Noisy Advice: Walking and Query Algorithms

Lucas Boczkowski, Uriel Feige, Amos Korman +1

We consider a search problem on trees in which the goal is to find an adversarially placed treasure, while relying on local, partial information. Specifically, each node in the tre…

cs.DS2009

An Optimal Labeling Scheme for Ancestry Queries

Pierre Fraigniaud, Amos Korman

An ancestry labeling scheme assigns labels (bit strings) to the nodes of rooted trees such that ancestry queries between any two nodes in a tree can be answered merely by looking a…