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Information Dynamics in the Interaction between a Prey and a Predator Fish
- Source :
- Entropy, Volume 17, Issue 10, Pages 7230-7241, Entropy, Vol 17, Iss 10, Pp 7230-7241 (2015)
- Publication Year :
- 2015
- Publisher :
- MDPI AG, 2015.
-
Abstract
- Accessing information efficiently is vital for animals to make the optimal decisions, and it is particularly important when they are facing predators. Yet until now, very few quantitative conclusions have been drawn about the information dynamics in the interaction between animals due to the lack of appropriate theoretic measures. Here, we employ transfer entropy (TE), a new information-theoretic and model-free measure, to explore the information dynamics in the interaction between a predator and a prey fish. We conduct experiments in which a predator and a prey fish are confined in separate parts of an arena, but can communicate with each other visually and tactilely. TE is calculated on the pair’s coarse-grained state of the trajectories. We find that the prey’s TE is generally significantly bigger than the predator’s during trials, which indicates that the dominant information is transmitted from predator to prey. We then demonstrate that the direction of information flow is irrelevant to the parameters used in the coarse-grained procedures. We further calculate the prey’s TE at different distances between it and the predator. The resulted figure shows that there is a high plateau in the mid-range of the distance and that drops quickly at both the near and the far ends. This result reflects that there is a sensitive space zone where the prey is highly vigilant of the predator’s position.
- Subjects :
- Information transfer
business.industry
transfer entropy
General Physics and Astronomy
lcsh:Astrophysics
lcsh:QC1-999
predation dynamics
Predation
Predatory fish
vigilance zone
lcsh:QB460-466
Forage fish
Statistics
information transfer
lcsh:Q
Transfer entropy
Information dynamics
Artificial intelligence
Information flow (information theory)
lcsh:Science
business
Predator
lcsh:Physics
Mathematics
Subjects
Details
- ISSN :
- 10994300
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- Entropy
- Accession number :
- edsair.doi.dedup.....1ea5349f8f0ec9646ae077a415a72dad