Multilevel evolutionary developmental optimization (MEDO): A theoretical framework for understanding preferences and selection dynamics

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📝 Original Info

  • Title: Multilevel evolutionary developmental optimization (MEDO): A theoretical framework for understanding preferences and selection dynamics
  • ArXiv ID: 1910.13443
  • Date: 2019-11-12
  • Authors: ** Adam Safron (Indiana University) **

📝 Abstract

What is motivation and how does it work? Where do goals come from and how do they vary within and between species and individuals? Why do we prefer some things over others? MEDO is a theoretical framework for understanding these questions in abstract terms, as well as for generating and evaluating specific hypotheses that seek to explain goal-oriented behavior. MEDO views preferences as selective pressures influencing the likelihood of particular outcomes. With respect to biological organisms, these patterns must compete and cooperate in shaping system evolution. To the extent that shaping processes are themselves altered by experience, this enables feedback relationships where histories of reward and punishment can impact future motivation. In this way, various biases can undergo either amplification or attenuation, resulting in preferences and behavioral orientations of varying degrees of inter-temporal and inter-situational stability. MEDO specifically models all shaping dynamics in terms of natural selection operating on multiple levels--genetic, neural, and cultural--and even considers aspects of development to themselves be evolutionary processes. Thus, MEDO reflects a kind of generalized Darwinism, in that it assumes that natural selection provides a common principle for understanding the emergence of complexity within all dynamical systems in which replication, variation, and selection occur. However, MEDO combines this evolutionary perspective with economic decision theory, which describes both the preferences underlying individual choices, as well as the preferences underlying choices made by engineers in designing optimized systems. In this way, MEDO uses economic decision theory to describe goal-oriented behaviors as well as the interacting evolutionary optimization processes from which they emerge. (Please note: this manuscript was written and finalized in 2012.)

💡 Deep Analysis

Deep Dive into Multilevel evolutionary developmental optimization (MEDO): A theoretical framework for understanding preferences and selection dynamics.

What is motivation and how does it work? Where do goals come from and how do they vary within and between species and individuals? Why do we prefer some things over others? MEDO is a theoretical framework for understanding these questions in abstract terms, as well as for generating and evaluating specific hypotheses that seek to explain goal-oriented behavior. MEDO views preferences as selective pressures influencing the likelihood of particular outcomes. With respect to biological organisms, these patterns must compete and cooperate in shaping system evolution. To the extent that shaping processes are themselves altered by experience, this enables feedback relationships where histories of reward and punishment can impact future motivation. In this way, various biases can undergo either amplification or attenuation, resulting in preferences and behavioral orientations of varying degrees of inter-temporal and inter-situational stability. MEDO specifically models all shaping dynamics in

📄 Full Content

1 MULTILEVEL EVOLUTIONARY DEVELOPMENTAL OPTIMIZATION (MEDO): A THEORETICAL FRAMEWORK FOR UNDERSTANDING PREFERENCES AND SELECTION DYNAMICS Adam Safron Indiana University

Abstract What is motivation and how does it work? Where do goals come from and how do they vary within and between species and individuals? Why do we prefer some things over others? MEDO is a theoretical framework for understanding these questions in abstract terms, as well as for generating and evaluating specific hypotheses that seek to explain goal-oriented behavior. MEDO views preferences as selective pressures influencing the likelihood of particular outcomes. With respect to biological organisms, these patterns must compete and cooperate in shaping system evolution. To the extent that shaping processes are themselves altered by experience, this enables feedback relationships where histories of reward and punishment can impact future motivation. In this way, various biases can undergo either amplification or attenuation, resulting in preferences and behavioral orientations of varying degrees of inter-temporal and inter-situational stability. MEDO specifically models all shaping dynamics in terms of natural selection operating on multiple levels—genetic, neural, and cultural—and even considers aspects of development to themselves be evolutionary processes. Thus, MEDO reflects a kind of generalized Darwinism, in that it assumes that natural selection provides a common principle for understanding the emergence of complexity within all dynamical systems in which replication, variation, and selection occur. However, MEDO combines this evolutionary perspective with economic decision theory, which describes both the preferences underlying individual choices, as well as the preferences underlying choices made by engineers in designing optimized systems. In this way, MEDO uses economic decision theory to describe goal-oriented behaviors as well as the interacting evolutionary optimization processes from which they emerge. (Please note: this manuscript was written and finalized in 2012.)

2 TABLE OF CONTENTS Introduction …………………………………………………………………………………………………………………….. 3 Multilevel Evolutionary Developmental Optimization (MEDO): A theoretical framework combining economic decision theory and Generalized Darwinism ………… 4 MEDO: Preferences as selective dynamics; Selective Dynamics as preferences …………………. 4 Economic decision theory ………………………………………………………………………………………………………………………………..4 Economic decision theory, expected utility, and preferences ……………………………………………………………………. 4 Bounded rationality and suboptimal choices……………………………………………………………………………………………….. 6 Action selection, expectations, and evolving preferences ………………………………………………………………………….. 6 Feedback dynamics and differential amplification of preferences ……………………………………………………………. 8 Generalized Darwinism …………………………………………………………………………………………………………………………………….9 Natural selection: replication, variation, selection………………………………………………………………………………………. 9 Natural selection, adaptation, and evolutionary utility ……………………………………………………………………………. 11 Natural selection, adaptive significance, and evolving selective pressures…………………………………………… 13 Optimization on multiple levels ………………………………………………………………………………………………………………….. 15 Multi-objective optimization problems and evolutionary engineering analyses …………………………………. 15 Evolutionary computation and fitness landscapes …………………………………………………………………………………… 17 Intentionality and evolving utility landscapes…………………………………………………………………………………………… 19 Generalized Darwinism and EDT: selective pressures as preferences; preferences as selective pressures ………………………………………………………………………………………………………………………………………………………… 21 Resolving the free will problem using MEDO: emergence, evolutionary explanations, and causation on ultimate and proximate levels ………………………………………………………….

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