Olfactory Search
摘要
The task of olfactory search is ubiquitous in nature and in technology, from animals in the quest of food or of a mating partner to robots searching for the source of hazardous fumes in a chemical plant. Here, we focus on the algorithmic approach to this task: we systematically review the different olfactory search strategies. Special emphasis is given to the formal description as a Partially Observable Markov Decision Process, which allows the computation of optimal actions and helps in clarifying the relationships between several effective heuristic search strategies.