Workshop on Computational Theories of Evolution

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source: Simons Institute     2014年3月27日
Workshop on Computational Theories of Evolution
Mar. 17 – Mar. 21, 2014
During the past decade, models and theories of evolution have been articulated which were inspired by computational considerations: examples are Valiant's evolvability, and the theory of mixability for the role of sex. The purpose of this workshop is to showcase and advance this strand of research, and also to expose it to the feedback and criticism of biologists and mathematicians. A second goal of the workshop is to highlight research questions in evolutionary biology which might benefit from computational insights and methodology, such as intractability proofs and novel algorithmic paradigms.
For more information, please visit http://simons.berkeley.edu/workshops/evolution2014-2.
These presentations were supported in part by an award from the Simons Foundation.

Presentation of Evolvability Leslie Valiant, Harvard University, Vitaly Feldman, IBM Almaden, Varun Kanade, UC Berkeley, and Elaine Angelino, Harvard University http://simons.berkeley.edu/talks/pres... 2:03:25
Molecular Errors, Cryptic Sequences, and Evolvability 53:45
Autocatalytic Sets and Models of Early Life 43:51
The Evolution of Evolvability 51:42
Presentation of Evolution and Algorithms 1:03:33
What Limits the Efficiency of Natural Selection? 39:33
Interaction-based Evolution: How Natural Selection and Non-accidental Mutation Work Together 1:07:09
Variation in Regulatory Information Within and Between Species 48:25
Birth and Death of Fragile Chromosomal Regions in Mammalian Evolution 59:15
Evolution of Dynamic Models for Embryonic Patterning and Their Geometric Representation 52:26
How to Treat Evolutionary Algorithms as Ordinary Randomized Algorithms 51:58
Measurement Scale and the Dissipation of Information Shape Biological Pattern 47:43
A New Research Program: Evolutionary Neurodynamics 46:44
Generalization of the Central Models of Evolutionary Biology in the (post)Genomic Era 1:00:13
Presentation of Evolvability 43:40
The Blessing and the Curse of Multiplicative Updates 58:56
Algorithms for Multityped Branching Processes 57:28
The Rate of Progress of Evolution 54:16
Evolution in Fluctuating Environments 46:55
The Adaptive Immune System as a Learning Algorithm 38:38
Satisfiability and Evolution 32:33
The Dynamics of Complex Adaptation 34:22
A Population Genetic Model of Disease Susceptibility and Other Quantitative Traits 49:53
Defensive Complexity in Antagonistic Coevolution 51:27
Darwinian Machine Learning: Principles of Machine Learning in Evo-devo, Evo-eco and Evolutionary... 57:23
A Few Comments (& Questions!) from a Condensed Matter Physicist 24:20
Non-Adaptive Evolvability 46:01
Complexity of Evolutionary Equilibria in Static Fitness Landscapes 30:35
Explaining Adaptation in Genetic Algorithms with Uniform Crossover 33:29

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