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Agent-Based Modeling: More Examples PSC 120 Jeff Schank
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Ovarian-Cycle Synchrony Does ovarian-cycle synchrony exist in mammals? The problem of cycle variability Ovarian cycles and female mate choice –The cost of synchrony
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Synchrony? Studies have reported synchrony in –Women –Norway rats –Golden hamsters –Golden lion tamarins –Chimpanzees All are fundamentally flawed and more recent studies have found no effects
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Original Results (1971)
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Does Menstrual Synchrony Exist?
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Does Menstrual Synchrony Exist? Continued…
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The Cost of Synchrony There are two types of fitness costs for synchronized females – Male quality – Mating opportunities To explore these costs, I built an ABM, based on J. B. Calhoun’s study: The Ecology and Sociology of The Norway Rat
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Calhoun’s Rats ABM Aims and Design –Ecologically realistic –Based on data –5 to 10 reproductive females at a given time –61 adult males (7 high, 12 medium, 42 low) –Movement is determined by “collapsing” preferences into a local probability space surrounding a model rat
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Two views of the Pen
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The Trails Map
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ABM Model
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Synchrony
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Synchrony by Chance
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Synchrony Distributions
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Male Quality & Synchrony
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Matings and Synchrony
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Male Quality & Cycle Length
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Matings & Cycle Length
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Conclusions Ovarian cycles may have evolved to facilitate female mate choice Synchrony has fitness costs Cycle variability may have fitness benefits in promiscuous mating systems
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The Development of Locomotion How do animals do what they do? How do we answer this question? Start simple and work to the complex If we want to understand how something works in space and time, it is often a good idea to build it or something like it. We cannot just build animals at different stages of development, but we can build models of them, which may help us understand them better (i.e., simulation, robotic)
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Rat Pups Born with very limited sensorimotor capabilities – Blind and deaf till days 13 to 15 – Legs cannot lift the body off the ground till after day 10 However, they can aggregate in huddles and thermoregulate
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Locomotor Development
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Behavior in a Temperature Controlled Arena: A Simple Paradigm
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Metrics Basic metric: tip of nose base of tail location Derived metrics – Activity – Object Contact – Speed – Aggregation – Conditional Probabilities
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7 and 10 Day Old Individual Locomotion: Examples Day 7 Day 10
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7 and 10 Day Old Individual & Group Locomotion Individual Group
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An Agent-Based Model
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Whole-Body Locomotion Kinematics
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Genetic Algorithms Arrange the parameters of the into a “chromosome” Create a population of models Perform mutation and crossover on pairs of models Run a number of simulations and choose the parameters that best fit the data
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Locomotion Kinematic Results Day 7Day 10 Individual Group
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7 and 10 Day Subgroup Formation Day 7Day 10
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7 and 10 Day Old Individual Locomotion: Examples Day 7 Day 10
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Model Examples Day 7 Day 10
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