Transient Behavior of Organisms Responding to Sudden Cues

Abstract

In their struggle for survival, living organisms display remarkable maneuvers while they interact with each other and their environment, leading to complex dynamics at multiple scales. But the mechanisms underlying the dynamics from sensing at the individual level to emergent behavior at the population level is not completely understood. The proposed research aims to understand how small organisms with limited sensory information can still make life-saving decisions by responding adequately to sudden environmental changes signaling an imminent threat or opportunity. The research will focus on the diverse behavior of planktonic copepods, tiny zooplankton thriving in the world s oceans. The specific objectives are to characterize the physical and chemical cues available to copepods and how they inform suitable responses to avoid predators, find potential mates, and capture food from sparse suspension. These problems will be addressed by formulating new mathematical models, and performing physical experiments and computer simulations. The models will approach the process of sensing as an inverse problem, and the possible behavioral responses will be predicted by accounting for ambiguities in the organisms perception and fluctuations in the environment. The models to be developed are sufficiently general so they are expected to apply to other organisms, including snails operating at much larger length and time scales. In addition, the models could support the design and development of autonomous robots capable of operating in highly dynamic environments.

Document Details

Document Type
DoD Grant Award
Publication Date
Oct 11, 2018
Source ID
W911NF1710442

Entities

People

  • Daisuke Takagi

Organizations

  • Army Contracting Command
  • United States Army
  • University of HawaiĘ»i System

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Marine Ecotoxicology
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control