📝 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 ………………………………………………………….
…(Full text truncated)…
Reference
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