Kenneth Letendre

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— Organisms that can more effectively exploit information about their environments to improve foraging success have a competitive and selective advantage over others. Thus, animals are expected to evolve strategies that use information to improve foraging success. We study how desert seed harvesters use information to improve the rate they collect seeds,(More)
Ants use individual memory and pheromone communication to achieve effective collective foraging. We implement these strategies as distributed search algorithms in robotic swarms. Swarms of simple robots are robust, scalable and capable of exploring for resources in unmapped environments. We test the ability of individual robots and teams of three robots to(More)
Desert seed-harvester ants, genus Pogonomyrmex, are central place foragers that search for resources collectively. We quantify how seed harvesters exploit the spatial distribution of seeds to improve their rate of seed collection. We find that foraging rates are significantly influenced by the clumpiness of experimental seed baits. Colonies collected seeds(More)
Collective foraging is a canonical problem in the study of social insect behavior, as well as in biologically inspired engineered systems. Pheromone recruitment is a well-studied mechanism by which ants coordinate their foraging. Another mechanism for information use is the memory of individual ants, which allows an ant to return to a site it has previously(More)
Evolutionary algorithms can adapt the behavior of individuals to maximize the fitness of cooperative multi-agent teams. We use a genetic algorithm (GA) to optimize behavior in a team of simulated robots that mimic foraging ants, then transfer the evolved behaviors into physical iAnt robots. We introduce positional and resource detection error models into(More)
Organisms process information in order to survive and reproduce. Biological computation is often distributed across multiple interacting agents, and is more adaptive, robust and scalable than traditional computation that relies on a central processing unit to schedule and allocate resources. In this chapter we highlight key features of computation in living(More)
Two-photon (2P) microscopy provides immunologists with 3D video of the movement of lymphocytes in vivo. Motility parameters extracted from these videos allow detailed analysis of lymphocyte motility in lymph nodes and peripheral tissues. However, standard parametric statistical analyses such as the Student's t-test are often used incorrectly, and fail to(More)
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