A Possible Artificial Intelligence Ecosystem Avatar: the Moorea case (IDEA)

High-throughput data collection techniques and largescale (cloud) computing are transforming our understanding of ecosystems at all scales by allowing the integration of multimodal data such as physics, chemistry, biology, ecology, fishing, economics and other social sciences in a common computational framework. We focus in this paper on a large scale data assimilation and prediction backbone based on Deep Stacking Networks (DSN) in the frame of the IDEA (Island Digital Ecosystem Avatars) project (Moorea Island), based on the subdivision of the island in watersheds and lagoon units. We also describe several kinds of raw data that can train and constrain such an ecosystem avatar model, as well as second level data such as ecological or physical indexes / indicators.

[1]  Yoshua Bengio,et al.  Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.

[2]  Po-Sen Huang,et al.  Random features for Kernel Deep Convex Network , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[3]  Yee Whye Teh,et al.  A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.

[4]  H. Ducklow,et al.  A nitrogen-based model of plankton dynamics in the oceanic mixed layer , 1990 .

[5]  Gökhan Tür,et al.  Towards deeper understanding: Deep convex networks for semantic utterance classification , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[6]  A. Barabasi,et al.  Universal resilience patterns in complex networks , 2016, Nature.

[7]  MODELING THE EROSION OF SHIELD VOLCANOES : THE TAHITI CASE , 2010 .

[8]  Wlodek Kofman,et al.  A two dimensional simulation of the CONSERT experiment (radio tomography of comet Wirtanen) , 1999 .

[9]  P. Hogeweg.  Cellular automata as a paradigm for ecological modeling , 1988 .

[10]  Willard L. Miranker,et al.  Beyond massive parallelism: numerical computation using associative tables , 1990, Parallel Comput..

[11]  V. Volterra.  Fluctuations in the Abundance of a Species considered Mathematically , 1926, Nature.

[12]  Yee Whye Teh,et al.  Rate-coded Restricted Boltzmann Machines for Face Recognition , 2000, NIPS.

[13]  Cumulative Perturbations Affecting a Spacecraft on a Mars Equatorial Orbit from the Waxing and Waning of the Polar Caps of the Planet , 2015 .

[14]  Jonathan R. Karr,et al.  A Whole-Cell Computational Model Predicts Phenotype from Genotype , 2012, Cell.

[15]  F ROSENBLATT,et al.  The perceptron: a probabilistic model for information storage and organization in the brain. , 1958, Psychological review.

[16]  Daniel Cressey.  Tropical paradise inspires virtual ecology lab , 2015, Nature.