Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.03374 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866929336377933824 |
|---|---|
| author | Celani, Antonio Panizon, Emanuele |
| author_facet | Celani, Antonio Panizon, Emanuele |
| contents | 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 Processes, which allows the computation of optimal actions and helps clarifying the relationships between several effective heuristic search strategies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_03374 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Olfactory search Celani, Antonio Panizon, Emanuele Biological Physics 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 Processes, which allows the computation of optimal actions and helps clarifying the relationships between several effective heuristic search strategies. |
| title | Olfactory search |
| topic | Biological Physics |
| url | https://arxiv.org/abs/2405.03374 |