Biological Search and Navigation: A Decision-Theoretic Perspective
ABSTRACT
We posit that biological search and navigation processes across diverse organisms are best understood as sequential decision-making
problems under uncertainty. Because organisms rely on noisy, partial observations of hidden environmental states, their behavior can be formally unified using the
probabilistic framework of Partially Observable Decision Processes. Grounding these theoretical abstractions in biology, we focus on navigation driven by chemical cues. Case studies range from chemotaxis in bacteria and eukaryotic cells to complex olfactory search processes in insects and mammals and dynamic
map-and-compass navigation in homing pigeons. Ultimately, this decision-theoretic perspective moves beyond
phenomenological descriptions, providing tools to infer the underlying computational mechanics, optimize normative models, and decipher the fundamental rules
governing biological behavior.
