Computational Mechanics in Food Webs: Difference between revisions
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== Overview == | == Overview == | ||
This project is about estimating causal states from population time series data and reconstruction of $\epsilon$-machines. One interesting question would be to look | This project is about estimating causal states from population time series data and reconstruction of $\epsilon$-machines. One interesting question would be to look at the causal states and find some correlations to nodes in a dynamic food web. Another question would be to quantify the population dynamics. | ||
We have have a frequentist [1] and a Bayesian [2] reconstruction algorithm. It would be interesting to see if they come up with the same result. As input data we can use a food web simulation we have seen in Neos lecture, wich is available [[http://www.foodwebs.org/index_page/wow2.html here]]. | We have have a frequentist [1] and a Bayesian [2] reconstruction algorithm. It would be interesting to see if they come up with the same result. As input data we can use a food web simulation we have seen in Neos lecture, wich is available [[http://www.foodwebs.org/index_page/wow2.html here]]. | ||
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== Who's interested == | == Who's interested == | ||
* [[Olaf Bochmann]] | * [[Olaf Bochmann]] | ||
* | * [[Joseph Lizier]] | ||
* | * [[John Mahoney]] | ||
* [[Gregor Obernosterer]] | |||
* [[Juergen Pahle]] | |||
== Presentation == | |||
[[Media:Example.ogg]] | |||
Latest revision as of 23:14, 28 June 2007
Overview
This project is about estimating causal states from population time series data and reconstruction of $\epsilon$-machines. One interesting question would be to look at the causal states and find some correlations to nodes in a dynamic food web. Another question would be to quantify the population dynamics.
We have have a frequentist [1] and a Bayesian [2] reconstruction algorithm. It would be interesting to see if they come up with the same result. As input data we can use a food web simulation we have seen in Neos lecture, wich is available [here].
Reading:
[1] C. R. Shalizi, K. L. Shalizi, and J. P. Crutchfield. An algorithm for pattern discovery in time series. 2002.
[2] C. C. Strelioff, J. P. Crutchfield, and A. Hubler. Inferring markov chains: Bayesian estimation, model comparison, entropy rate, and out-of-class modeling. 2007.