THE NATURAL SELECTION: BEHAVIOR ANALYSIS AMONG THE NATURAL SCIENCES

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THE NATURAL SELECTIONBEHAVIOR ANALYSIS AMONG
THE NATURAL SCIENCES

• M. Jackson Marr
• School of Psychology
• Georgia Tech
• Atlanta, GA 30332-0170
• USA
• mm27_at_prism.gatech.edu

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LECTURE TOPICS

• BEHAVIOR ANALYSIS AS A NATURAL SCIENCE
• CONTINGENCY THE FUNDAMENTAL
• EXPLANATORY CONCEPT
• 3. DIMENSION IN ACTION THE PROBLEM
• OF BEHAVIORAL UNITS
• 4. MODELS IN BEHAVIOR ANALYSIS
• 5. REDUCTION AND BEHAVIOR ANALYSIS

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In understanding behavior analysis as a natural
science, we need to examine ties, conceptual and
otherwise, between behavior analysis and other
natural sciencesthis is my overall theme.
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WHAT IS A NATURAL SCIENCE?
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SOME ISSUES TO CONSIDER

• 1. What is a Natural Science?
• 2. Ontology, Epistemology, and Patterns of
  Explanation.
• 3. Behavior Analysis as a Biological Science
• 4. Contingency The Fundamental
  Explanatory Concept
• 5. The Problem of Behavioral Units
• 6. The Role of Symmetry
• 7. Dynamical Systems
• 8. Mathematical Models
• 9. Problems of Reductionism
• 10. Scientific and Mathematical Verbal Behavior
• 11. Creativity in the Sciences and Mathematics
• I plan to discuss these, given time.

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ONTOLOGY, EPISTEMOLOGY, AND PATTERNS OF
EXPLANATION Realism vs. Pragmatism, and
Contextualism vs. Mechanism
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ELEMENTS OF CONTEXTUALISM

• 1. The ongoing act in context as the unit of
  analysis.
• 2. Focus on the whole event.
• 3. Sensitivity to the role of context in
  understanding the event.
• 4. Successful working as a pragmatic truth
  criterion.

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WHAT KINDS OF MECHANISMS BEHAVIOR ANALYSIS AS A
BIOLOGICAL SCIENCE
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GENERAL FUND OF BIOLOGICAL EXPLANATION

• 1. Molecular (biochemical, biophysical)
• 2. Cellular functions
• 3. Tissue/organ functions
• 4. Morphogenic/developmental
• 5. Behavioral/environmental
• 6. Species adaptation/evolution

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SOME SOURCES OF BIOLOGICAL VARIATION

• MEIOSIS PROCESSES (e.g., recombination, linkage
  distance)
• SEGREGATION (e.g., independent assortment,
  dominance, incomplete dominance, epistasis,
  pleiotropy)
• NON-MENDELIAN PROCESSES (e.g., cytoplasmic
  inheritance, dependent assortment)
• CHROMOSOMAL VARIATIONS (e.g., polyploidy,
  deletions, duplications, inversions,
  translocations)
• MUTATIONS (e.g., transitions, transversions,
  tautometric, regulatory effects)
• ALTERNATIVE SPLICING
• QUANTITATIVE (e.g., polygenic expression, genetic
  drift, gene-environment interaction)

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MORE SOURCES OF BIOLOGICAL VARIATION

• DEVELOPMENTAL DYNAMICS (e.g., evo-devo)
• ALLOPATRIC, PARAPATRIC, AND SYMPATRIC ISOLATION
• IN UTERO HISTORY
• STOCHASTIC / CHAOTIC PHYSIOLOGICAL PROCESSES

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SOME SOURCES OF BEHAVIORAL VARIATION

• 1. REFLEX PATTERNS AND THRESHOLDS
• 2. SPECIES-SPECIFIC SENSORY / MOTOR PROGRAMS
• 3. CONTINGENCIES AND DIFFERENTIAL SENSITIVITY
  
• TO THEM
• 4. SHAPING VARIATION AS A RESPONSE CLASS
• 5. SELF-ORGANIZATION PROCESSES EMERGENCE
• 6. SOCIAL/CULTURAL DYNAMICS
• 7. A HOST OF INDIVIDUAL DIFFERENCES RELATED TO
• ALL THE ABOVE AND MORE

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COMPUTATIONAL MODELING

• NEURAL NETWORKS
• CELLULAR AUTOMATA
• DYNAMIC PROGRAMING
• DYNAMIC STATE VARIABLE MODELS
• GENETIC ALGORITHMS
• SIMULATED ANNEALING
• MONTE CARLO METHODS
• STATISTICAL MECHANICS OF LEARNING

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PHYSICS VS. BIOLOGY/BEHAVIOR Mayrs
Distinctions

• PHYSICS
• Deterministic
• Reductive
• Mechanistic
• Immediate Causation
• SIMPLICITY

• BIOLOGY
• Stochastic
• Emergent
• Selectionistic
• Historical Causation
• COMPLEXITY

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CODA So What?
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CONSEQUENCE-DRIVEN SYSTEMS Stevo Bozinovski (1995)
REINFORCEMENT LEARNING R.S. Sutton A.G.
Barto (1998)