Download Rationality & Evolution

Un « fait frappant »…
« The most striking fact about the
relationship between evolutionary
game theory and economic game
theory is that, at the most basic level,
a theory built of hyperrational actors
and a theory built of possibly nonrational actors are in fundamental
agreement. This fact has been widely
noticed, and its importance can
hardly be overestimated »
(Skyrms 2000, p. 273)
1
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
2
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
3
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Le « sophisme naturaliste »
« All that the evolution-hypothesis tells us is
that certain kinds of conduct are more
evolved than others; […]. Yet [Mr. Spencer]
tells us that one of the things he has proved
is that conduct gains ethical sanction in
proportion as it displays certain
characteristics. What he has tried to prove is
only that in proportion as it displays those
characteristics, it is more evolved, it is plain,
then, that Mr. Spencer identifies the gaining
of ethical sanction with the being more
evolved. »
Moore, Principia Ethica, pp. 48-4.
4
L’heuristique de la personnalisation
permet d’échapper au sophisme
naturaliste…
« If natural selection controls which of
traits T, A1, A2,…, An, evolves in a
given population, then T will evolve,
rather than the alternatives listed, if
and only if a rational agent who
wanted to maximize fitness would
choose T over A1, A2,…, An »
(Sober 1998, pp. 408f.)
5
« Rational choice only gets value out by
optimizing the value input captured by
the agent’s preferences. Conversely,
what evolution optimizes is only a
value if reproductive fitness is
valued. »
(p. 3)
Fitness individuelle vs. fitness
collective
« And as natural selection works solely
by and for the good of each being, all
corporeal and mental endowments
will tend to progress towards
perfection »
(Darwin 1859,p. 489)
« The economists of Darwin’s time
tended to think that since a society is
‘nothing but’ a collection of
individuals, the society will maximize
its well-being if each individual
endeavors to maximize his welfare.
…»
6
(Sober 1984)
Dépendance envers la
fréquence:
la
tragédie du pré communal
« [T]he rational herdsman concludes that the
only sensible course for him to pursue is to
add another animal to his herd. And
another.... But this is the conclusion reached
by each and every rational herdsman
sharing a commons. Therein is the tragedy.
Each man is locked into a system that
compels him to increase his herd without
limit -- in a world that is limited. Ruin is the
destination toward which all men rush, each
pursuing his own best interest in a society
that believes in the freedom of the
commons. Freedom in a commons brings
ruin to all. »
Garrett Hardin, Science, 162(1968):1243-1248.
7
By the way, c’est
exactement ce qui est arrivé
à nos morues…
8
L’évolution optimise quand
même la rationnalité…
« While grazers’ and fishers’
welfare will not be maximized by
evolution in a commons, their
rationality should be. Rationality,
after all, is the perfection of just
those abilities useful for
exploiting any situation, including
social dilemmas. »
(p. 4)
9
Le « rationalisme
évolutionniste »
« Creatures inveterately wrong in
their inductions have a pathetic
but praise-worthy tendency to die
before reproducing their kind. »
(Quine 1969)
« Natural selection guarantees that
most of an organism's beliefs will
be true, most of its strategies
rational »
(Dennett 1987)
10
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
11
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Le problème de l’égalité
(numérique) des sexes
« [G]enerally females are the scarcity
constraint on reproduction, so we
should expect fewer males in an
optimum sex mix. »
(p. 5)
« I formerly thought that when a
tendency to produce the two sexes in
equal numbers was advantageous to
the species, it would follow from
natural selection, but I now see that
the whole problem is so intricate that
it is safer to leave its solution for the
future »
12
(Darwin 1871)
13
Problème parallèle :
séparer le gâteau
• On sait que, pour être juste, il
faut séparer le gâteau 50-50,
mais la théorie des jeux ne nous
dit pas pourquoi.
• Équilibre de Nash:
14
« We have an equilibrium in informed
rational self-interest if each of our
claims are optimal given the other’s
claim. In other words, given my
claim you could not do better by
changing yours and given your
claim I could do no better by
changing mine. »
Problème: il y a une infinité
d’équilibres de Nash
Demande A
1
00
15
Demande B
1
Est-ce que c’est moi qui ne
comprend pas?
« Skyrms argues that rational choice cannot
answer this basic question about fairness »
Utilité attendue
(p. 6)
16
Stratégie (demande x)
Payoffs par stratégie, en
termes de reproductive
fitness
17
Demande
1/3
Demande
1/2
Demande
2/3
Modeste
Demande
1/3
1/3
1/3
1/3
Impartial
Demande
1/2
1/2
1/2
0
Cupide
Demande
2/3
2/3
0
0
Fitness attendues, avec
distribution égale des
stratégies
18
Demande
1/3
Demande
1/2
Demande
2/3
Fitness
attendue
Modeste
Demande
1/3
1/3
1/3
1/3
1/3
Impartial
Demande
1/2
1/2
1/2
0
1/3
Cupide
Demande
2/3
2/3
0
0
2/9
Fitness attendues, une fois
que les cupides sont
disparus
Modeste
Demande
1/3
Demande
1/3
Demande
1/2
Demande
2/3
Fitness
attendue
1/3
1/3
1/3
1/2
1/2
1/2
SES
19
Impartial
Demande
1/2
Cupide
Demande
2/3
Une version en automate
cellulaire
http://www.ags.uci.edu/~jalex/lattice-models/
20
Dynamique de l’égalité
Demande 1/2
Demande 1/3
21
Demande 2/3
C’est la même chose pour
le sex ratio
(Fisher 1930, p. 142)
22
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
23
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Rationality as (economic)
game theory
« Evolution is only isomorphic to
rationality if we restrict the range
of both concepts. » (p. 8)
• Danielson choisi de se limiter à la
rationalité dans les interactions,
qui est le problème le plus
complexe de la rationalité.
24
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
25
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
La théorie des jeux
s’applique mieux à la
biologie
qu’à
l’économie…
« There are two
reasons
for this.
26
– First, the theory requires that the values of
different outcomes […] be measured on a single
scale. In human application, this measure is
provided by ‘utility’ – a somewhat artificial and
uncomfortable concept: in biology, Darwinian
fitness provides a natural and genuinely onedimensional scale […].
– Secondly, and more importantly, in seeking the
solution of a game, the concept of human
rationality is replaced by that of evolutionarily
stability. The advantage here is that there are
good theoretical reasons to expect populations to
evolve to stable states, whereas there are grounds
for doubting whether human beings always
behave rationally. »
(Maynard Smith 1982, p. vii).
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
27
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Qu’est-ce qu’une SES?
« It is a strategy such that, if most
of the members of a population
adopt it, there is no ‘mutant’
strategy that would give higher
reproductive fitness »
(Maynard Smith & Price 1973, p. 15)
« For distinct strategies x and y
and utility function u,
1) u(x,x) ≥ u(y,x)
2) If u(x,x) = u(y,x) then u(x,y) > u(y,y) »
(p. 10)
28
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
29
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Economic evolutionary
game theory
« Where biological evolutionary
game theory is intentionally
broad in the scope of its agents,
economic evolutionary game
theory focuses more narrowly on
explaining human action.
[E]conomic evolutionary game
theory modeling is based on a
human learning dynamic. »
(p. 11-12)
30
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
31
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Un pas de plus:
généralisme évolutionniste
« [Fair division’s] strong stability properties
guarantee that is an attracting equilibrium
in the replicator dynamics, but also make
the details of the dynamics unimportant.
Fair division will be stable in any dynamics
with a tendency to increase the proportion
(or probability) of strategies with greater
payoffs … For this reason, the Darwinian
story can be transposed into the context of
cultural evolution, in which imitation and
learning may play an important role in the
dynamics »
(Skyrms 1996 , p. 11)
32
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
33
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Retour sur la citation de
départ
« The most striking fact about the relationship
between evolutionary game theory and
economic game theory is that, at the most
basic level, a theory built of hyper-rational
actors and a theory built of possibly nonrational actors are in fundamental
agreement. This fact has been widely
noticed, and its importance can hardly be
overestimated. Criticism of game theory
based on the failure of rationality
assumptions must be reconsidered from the
viewpoint of adaptive processes. There are
many roads to the Nash equilibrium
concept, only one of which is based on
highly idealized rationality
assumptions »
34
(Skyrms 2000, p. 273)
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
35
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Symétrie
« A single population evolutionary
setting imposes a symmetry
requirement which selects Nash
equilibria which appear
implausible in other settings »
(Skyrms 2000, p. 273)
« [Evolution] often (but not
always) leads to selection of fair
division in a simple bargaining
game. »
(Skyrms 1996, ch. 1)
36
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
37
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Deux différences: stratégies
faiblement dominées et
rationalité modulaire
• “[R]efinements of the Nash
equilibrium are handled
differently.
– Standard evolutionary dynamics
[…] does not guarantee elimination
of weakly dominated strategies.
– [E]volutionary dynamics need not
eliminate strategies which fail the
test of sequential rationality »
(Skyrms 2000, p. 273)
38
Concept de dominance
• When a player tries to choose the "best" strategy
among a multitude of options, that player may
compare two strategies A and B to see which one is
better.
– B dominates A: choosing B always gives at least as good
an outcome as choosing A. There are 2 possibilities:
• B strictly dominates A: choosing B always gives a better
outcome than choosing A, no matter what the other
player(s) do.
• B weakly dominates A: There is at least one set of
opponents' action for which B is superior, and all other
sets of opponents' actions give A and B the same payoff.
• This notion can be generalized beyond the
comparison of two strategies.
– Strategy B is strictly dominant if strategy B strictly
dominates every other possible strategy.
– Strategy B is weakly dominant if strategy B dominates
all other strategies, but some are only weakly
dominated.
http://en.wikipedia.org/wiki/Dominance_(game_theory)
39
Rationalité modulaire
« In a credible contingency plan for a situation in which
an agent faces a sequence of choices, her plan should
specify a rational choice at each choice point, relative
to her situation at that choice point »
(Skyrm 1996, p. 24)
40
Le jeu de l’ultimatum
Gamesman S1
Si joueur 2
Offre 1
Accepte tout
S2 Offre 1
Rejette tout
S3 Offre 1
Accepte 5, rejette 1
Mad Dog
S4 Offre 1
Rejette 5, accepte 1
Easy Rider
S5 Offre 5
Accepte tout
S6 Offre 5
Rejette tout
S7 Offre 5
Accepte 5, rejette 1
S8 Offre 5
Rejette 5, accepte 1
Fairman
41
Si joueur 1
Le jeu de l’ultimatum:
répartition égale des
stratégies
Si joueur 1
Si joueur 2
Offre 1
Accepte tout
12.5
S2 Offre 1
Rejette tout
12.5
S3 Offre 1
Accepte 5, rejette 1
12.5
Mad Dog
S4 Offre 1
Rejette 5, accepte 1
12.5
Easy Rider
S5 Offre 5
Accepte tout
12.5
S6 Offre 5
Rejette tout
12.5
S7 Offre 5
Accepte 5, rejette 1
12.5
S8 Offre 5
Rejette 5, accepte 1
12.5
Gamesman S1
Fairman
42
% init.
Le jeu de l’ultimatum:
les Mad Dogs (faiblement
dominés) survivent!
Si joueur 1
Si joueur 2
Offre 1
Accepte tout
12.5
87
S2 Offre 1
Rejette tout
12.5
0
S3 Offre 1
Accepte 5, rejette 1
12.5
0
Mad Dog
S4 Offre 1
Rejette 5, accepte 1
12.5
13
Easy Rider
S5 Offre 5
Accepte tout
12.5
0
S6 Offre 5
Rejette tout
12.5
0
S7 Offre 5
Accepte 5, rejette 1
12.5
0
S8 Offre 5
Rejette 5, accepte 1
12.5
0
Gamesman S1
Fairman
43
% init. % final
En version automate
cellulaire
http://www.ags.uci.edu/~jalex/lattice-models/
44
Le jeu de l’ultimatum:
haute proportion initiale de
fairmen
Si joueur 1
Si joueur 2
Offre 1
Accepte tout
32
S2 Offre 1
Rejette tout
2
S3 Offre 1
Accepte 5, rejette 1
10
Mad Dog
S4 Offre 1
Rejette 5, accepte 1
2
Easy Rider
S5 Offre 5
Accepte tout
10
S6 Offre 5
Rejette tout
2
S7 Offre 5
Accepte 5, rejette 1
40
S8 Offre 5
Rejette 5, accepte 1
2
Gamesman S1
Fairman
45
% init.
Le jeu de l’ultimatum:
les fairmen (faiblement dominés)
survivent
Si joueur 1
Si joueur 2
Offre 1
Accepte tout
32
0
S2 Offre 1
Rejette tout
2
0
S3 Offre 1
Accepte 5, rejette 1
10
0
Mad Dog
S4 Offre 1
Rejette 5, accepte 1
2
0
Easy Rider
S5 Offre 5
Accepte tout
10
43.5
S6 Offre 5
Rejette tout
2
0
S7 Offre 5
Accepte 5, rejette 1
40
56.5
S8 Offre 5
Rejette 5, accepte 1
2
0
Gamesman S1
Fairman
46
% init. % final
Dynamique de l’ultimatum
47
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
48
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
« Rational choice is concerned with the
intended outcomes of action.
Selection mechanisms operate
through actual outcomes. In
explanations of animal behavior,
where intentions have at best a
minimal place, actual outcomes must
bear most of the explanatory burden.
It is more controversial which
mechanism is the most important in
the study of human action »
(Elster 1989, p. 71)
49
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
50
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Méthodes: simulations vs.
modèles
« Roughly, the contrast between
rationality and evolution projects
onto methods, with evolution
characterized more by
simulations and rationality by
more formal models. »
(p. 16)
51
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
52
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Axelrod
• Axelrod 1984: The Evolution of Cooperation
– Évolution des stratégies dans le dilemme du
prisonnier itéré;
– Stratégie gagnante: TIT-FOR-TAT
• Critiques:
– On connaissait déjà le folk theorem…
– Trop d’emphase sur TIT-FOR-TAT;
• Binmore 1998:
53
« The folk theorem of game theory proved by
several authors simultaneously in the early fifties
… describes in precise detail all of the outcomes
of a repeated game that can be sustained as
equilibria. [Axelrod] did us the service of focusing
our attention on the importance of evolution in
selecting an equilibrium from the infinitude of
possibilities whose existence is demonstrated by
the folk theorem. »
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
54
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Évolution et rationalité
« Stepping back, it is obvious that the
complete picture must include both;
evolution has historically produced
some rational agents. So the question
arises, how might one model the
interaction between evolution and
rationality? Given the difference in
time scales of the two processes, a
natural way to approach the relation
of rationality and evolution is by a two
level model.»
(p. 18)
55
Exemple de modélisation multiniveau
56
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
57
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Mieux que rationnel?
« One point is particularly important for economists to
appreciate: it can be demonstrated that ‘rational’
decision-making methods … are computationally very
weak: incapable of solving the natural adaptive
problems our ancestors had to solve reliably in order
to reproduce… This poor performance on most
natural problems is the primary reason why problemsolving specializations were favored by natural
selection over general purpose problem-solvers. ….
On evolutionarily recurrent computational tasks,
such as object recognition, grammar acquisition, or
speech comprehension the human mind greatly
outperforms the best artificial problem-solving
systems that decades of research have produced, and
it solves large classes of problems that even now no
human-engineered system can solve at all. »
(Cosmides et Tooby 1994)
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Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
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5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Pourquoi la rationalité est
normative, mais pas
l’évolution?
• Comparez:
« Pourquoi devrais-je me préoccuper
d’être copié? »
« Pourquoi devrais-je me préoccuper
de mes propres préférences? »
60
Les paradoxes de la
rationalité
• La rationalité est autoréférentielle: il est rationnel
d’être rationnel.
– Notre concept de rationalité est
fondé sur un « mélange d’intuition,
d’analogies et d’idéologie »
(Samuelson 1997)
– L’évolution peut peut-être
• Modifier ces intuitions
• Nous éclairer sur leur source
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L’influence du positif sur le
normatif
« If I have strong reasons, based on
evolutionary equilibrium selection, to
expect you to choose a particular
strategy, normative rationality gives
me a reason to coordinate with your
choice. »
(p. 22)
« If possibility is construed generously
we have utopian theory. Those who
would deal with ‘men as they are’
need to work with a more restrictive
sense of possibility. »
(Skyrms 1996, pp. 108-9)
62
Rationality & Evolution
1 Two Optimizing Processes
2 Isomorphism
2.1 Sex and Fairness
2.1.1 Rationality as (economic) game theory
2.2 Evolution as evolutionary game theory
2.2.1 Biological evolutionary game theory
2.2.2 Economic evolutionary game theory
2.3 Evolutionary Generalism
2.4 Why isomorphism is important
3 Differences
3.1 Symmetry
3.2 Dominated Strategies
3.3 Actual Fitness and Intended Outcomes
4 Simulations and multi-level models
4.1 Axelrod
4.2 A methodology: Multi-level modeling
4.3 Computational Differences
5 Normativity
63
5.1 Normative Rationality vs. Descriptive Evolution
5.2 What are the prospects for convergence?
Chacun tire la couverte…
« [T]he combination of education and evolution drives
society in the direction of [game] theory. …. A widely
applicable theory of games would, of necessity,
involve a strong element of self-prophecy in the sense
that the existence of the theory itself would be partly
responsible for bringing about stabilizing the event
which it ‘predicts’ »
(Binmore 1990, p. 18f).
« One might then reasonably expect to see [constrained
choice in cooperative dilemmas] drive out more
costly precommitment and enforcement methods,
and this through nothing more than what economists
like to describe as the ordinary competitive
process. »
(McLennen 1998)
64
Fin.
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