Adaptive Individuals in Evolving Populations Models and Algorithms 1st Edition by Richard K Belew, Melanie Mitchell ISBN 0201483696 9780201483697

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ISBN 10: 0201483696 
ISBN 13: 9780201483697
Author: Richard K Belew, Melanie Mitchell

Adaptive Individuals in Evolving Populations Models and Algorithms 1st Table of contents:

CHAPTER 1: INTRODUCTION

1. book overview: form and content

2. major themes of this book
    2.1 direct versus indirect interactions between genotypic and phenotypic adaptations
    2.2 behavior as a phenotypic trait
    2.3 interactions between learning and evolution
    2.4 “coevolution” between organisms and their environments
    2.5 are learning and evolution two faces of same coin?

3. caveats

4. the benefits of interdisciplinary research
   references

BIOLOGY

CHAPTER 2: ADAPTIVE COMPUTATION IN ECOLOGY AND EVOLUTION: A GUIDE FOR FUTURE RESEARCH

1. what ecological and evolutionary models do

2. issues in ecology
    2.1 topics for idea models
    2.2 topics for minimal system models

3. issues in evolutionary biology
   references

REPRINTED CLASSICS

CHAPTER 3: THE CLASSICS IN THEIR CONTEXT, AND IN OURS
the climate
the ideas
conclusions
references

CHAPTER 4: OF THE INFLUENCE OF THE ENVIRONMENT ON THE ACTIVITIES AND HABITS OF ANIMALS, AND THE INFLUENCE OF THE ACTIVITIES AND HABITS OF THESE LIVING BODIES IN MODIFYING THEIR ORGANIZATION AND STRUCTURE

CHAPTER 5: A NEW FACTOR IN EVOLUTION
section i.
ontogeny: organic selection (see baldwin, 1895a, chap vii.)
effects of organic selection
section ii.
phylogeny: physical heredity
section iii.
social heredity
section iv.
the process of organic selection
section v.
section vi.
the matter of terminology
organic selection
social heredity
references

CHAPTER 6: ON MODIFICATION AND VARIATION1

CHAPTER 7: CANALIZATION OF DEVELOPMENT AND THE INHERITANCE OF ACQUIRED CHARACTERS
references

CHAPTER 8: THE BALDWIN EFFECT
historical introduction
terminology and definition
supposed examples of the baldwin effect
status of the baldwin effect in evolutionary theory
literature cited

CHAPTER 9: THE ROLE OF SOMATIC CHANGE IN EVOLUTION1
summary
references

NEW WORK

preface to chapter 10
references

CHAPTER 10: A MODEL OF INDIVIDUAL ADAPTIVE BEHAVIOR IN A FLUCTUATING ENVIRONMENT

1. introduction

2. the environment

3. individual fitness

4. individual strategies

5. a semi-optimal strategy

6. multiplicative fitnesses

7. randomly varying fitnesses

8. special case: two environmental states

9. errors in information about parameters

10. concluding remarks
    acknowledgment
    appendix a: proofs of results 1 and 2
    appendix b: proof of result 3
    references

preface to chapter 11
references

CHAPTER 11: THE BALDWIN EFFECT IN THE IMMUNE SYSTEM: LEARNING BY SOMATIC HYPERMUTATION

1. introduction

2. the immune system and clonal selection

3. the binary immune system

4. the experiment

5. the results

6. discussion
   acknowledgments
   references

preface to chapter 12

CHAPTER 12: THE EFFECT OF MEMORY LENGTH ON INDIVIDUAL FITNESS IN A LIZARD

1. introduction

2. the anolis lizards system
    2.1 a lizard’s dilemma
    2.2 the theoretical solution
    2.3 the problem of attainability
    2.4 a rule of thumb

3. simulation
    3.1 simulation parameters
    3.2 simulation results

4. discussion
   acknowledgments
   references

appendix to chapter 12: “the effect of memory length on individual fitness in a lizard”
definitions and simplifications

preface to chapter 13

CHAPTER 13: LATENT ENERGY ENVIRONMENTS

1. introduction

2. modeling environmental complexity

3. modeling the life process
    3.1 behavior
    3.2 learning

4. modeling the evolutionary process

5. emerging features
    5.1 carrying capacity
    5.2 fitness measures
    5.3 age distribution

6. current and future directions
   acknowledgments
   references

PSYCHOLOGY

CHAPTER 14: THE CAUSES AND EFFECTS OF EVOLUTIONARY SIMULATION IN THE BEHAVIORAL SCIENCES

1. introduction

2. causes for the advent of simulation in studying the evolution of behavior

3. fruitful areas for exploration with evolutionary simulations

4. effects of simulating the evolution of learning and other adaptive processes
   acknowledgments
   references

REPRINTED CLASSICS

preface to chapters 15 and 16
acknowledgment
references

CHAPTER 15: EXCERPTS FROM “THE PRINCIPLES OF BIOLOGY”
table 1

CHAPTER 16: EXCERPTS FROM “THE PRINCIPLES OF PSYCHOLOGY”

CHAPTER 17: WILLIAM JAMES AND THE BROADER IMPLICATIONS OF A MULTILEVEL SELECTIONISM
a hierarchy of selectors
fools rush in
conclusions
references

CHAPTER 18: EXCERPTS FROM “THE PHYLOGENY AND ONTOGENY OF BEHAVIOR”
the provenance of behavior
some problems raised by phylogenic contingencies
identifying phylogenic and ontogenic variables
interrelations among phylogenic and ontogenic variables
misleading similarities
note 7.1: nature or nurture?
note 7.2: species-specific behavior
note 7.3: interrelations among phylogenic and ontogenic variables
note 7.4: aggression
note 7.5: a possible example of programmed phylogenic contingencies
references

preface to chapter 19
references

CHAPTER 19: EXCERPTS FROM “ADAPTATION AND INTELLIGENCE: ORGANIC SELECTION AND PHENOCOPY”
preface
preliminaries

1. genotype and epigenetic system

preface to chapter 20
references

CHAPTER 20: SELECTIVE COSTS AND BENEFITS IN THE EVOLUTION OF LEARNING
i. introduction
ii. learning and evolution—historical background and current concerns
iii. an ecological conception of learning
iv. cost-benefit analysis and the evolution of adaptations
v. the selective benefits of learning
 a. adaptation to environmental variability
 b. sexual selection
 c. lack of variation for other adaptive solutions
vi. the selective costs of learning
 a. delayed reproductive effort and/or success
 b. increased juvenile vulnerability
 c. increased parental investment in each offspring
 d. greater complexity of the central nervous system
 e. greater complexity of the genome
 f. developmental fallibility
vii. learning and the adaptive complex
 a. interactions of selective pressures and adaptive traits
 b. limits on adaptive precision
viii. implications for the study of learning
acknowledgments
references

NEW WORK

preface to chapter 21
evolution of learning via sexual selection
the effect of learning on evolution
references

CHAPTER 21: SEXUAL SELECTION AND THE EVOLUTION OF LEARNING

1. introduction

2. the evolution of sexually selected forms of learning
    2.1 adaptive functions of mate preference learning
    2.2 the evolution of sexual (parental) imprinting

3. effects of sexually selected learning on evolution
    3.1 sexual imprinting and speciation
    3.2 other forms of sexually selected learning and their evolutionary effects

4. conclusions
   acknowledgments
   references

preface to chapter 22

CHAPTER 22: DISCONTINUITY IN EVOLUTION: HOW DIFFERENT LEVELS OF ORGANIZATION IMPLY PREADAPTATION

1. introduction

2. describing organisms at multiple levels

3. the model
    3.1 genetic model
    3.2 developmental model
    3.3 neural model
    3.4 behavioral model
    3.5 hierarchical relation among levels

4. results of simulations

5. discussion
   acknowledgments
   references

preface to chapter 23

CHAPTER 23: THE INFLUENCE OF LEARNING ON EVOLUTION

1. evolution and learning

2. evolution’s influence on learning

3. learning’s influence on evolution

4. how learning to predict can have an effect on evolution
   references

COMPUTER SCIENCE

CHAPTER 24: COMPUTATION AND THE NATURAL SCIENCES

1. what can computer science offer the natural sciences?
   computer programs as models
   models as communicative devices
   computation as a framework for natural science
   what can the natural sciences offer computer science?
   references

REPRINTED CLASSICS

preface to chapter 25
references

CHAPTER 25: HOW LEARNING CAN GUIDE EVOLUTION

1. introduction

2. an extreme and simple example

3. a simulation

4. discussion
   acknowledgments
   references

natural selection: when learning guides evolution
references

NEW WORK

preface to chapter 26

CHAPTER 26: SIMULATIONS COMBINING EVOLUTION AND LEARNING

1. introduction

2. evolution and learning
    2.1 evolution finds optimal behavior
    2.2 learning finds optimal behavior
    2.3 combination speeds adaptation
    2.4 combination solves more general problems

3. architectures for learning
    3.1 supervised learning
    3.2 reinforcement learning
    3.3 unsupervised learning
    3.4 evolutionary reinforcement learning

4. conclusion
   references

preface to chapter 27
references

CHAPTER 27: OPTIMIZATION WITH GENETIC ALGORITHM HYBRIDS THAT USE LOCAL SEARCH
introduction
genetic algorithm hybrids with local search
experimental design
floating point ga
local search algorithms
test problem
experimental factors

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