Overview
Research Question: How can we formalize the evolution of heredity, environment, and phenotype through time and across biological levels? Goal: Extend Variational Neuroethology (Ramstead et al. 2017) to specify a tractable general framework for all Evolutionary studies, Biological and Otherwise. This would allow us to integrate current data across systems and suggest new measurements/experiments/systems.
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Methods and contributions
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Findings and contributions
- The talk claims EcoEvoDevo is stuck in a locally-optimizing regime because of an incoherent genotype-phenotype-environment and fitness framing.
- It argues the data, theory and philosophy already exist for a tractable generalized model of evolution, with the challenge being integrating VNE with classical theory using limited data.
- It critiques VNE's human-cognition case study as not yet operationalized for actual data and unclear for other evolutionary systems.
- It proposes MVEE (Multilevel Variational Evolutionary Ecology) as a framework combining VNE, EcoEvoDevo, collective behavior and machine learning.
Methods
- Extension of Variational Neuroethology (Ramstead et al. 2017) to evolution — Builds the proposed MVEE framework by extending VNE toward a general framework for evolutionary studies.
- Genotype-Environment-Phenotype tensor representation through time — Represents evolving systems as a dynamic multiscale G-E-P tensor over time, using only measurable quantities instead of fitness.
- Pairing of state models and process models across scales — Distinguishes predictive state theories (e.g. R = h2S) from algorithmic process theories and combines them via coarse-graining.
- Proposed compute-graph (TensorFlow) machine-learning architecture — Proposes a single integrated ML framework on existing biological data to jointly consider coarse-grained state and process models.
- Worked example: 'Pogo Foraging' state/process models across three scales — Sketches state and process models for one ant colony over a day, a population of colonies over a summer, and populations over intergenerational time.
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- 2018_MVEE.pdf PDF · 6.72 MiB · extracted-text source
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