Changing the Rules of the Game
Dr. Marco A. Janssen
Department of Spatial Economics
Research questions
• How do rules emerge, get selected and be
remembered in social ecological systems?
• What can we learn from (computational
models of) immune systems and language
development?
Contents
• Puzzles from empirical studies of common
pool resources.
• Immune system
• Language development
• Methodology
• Modeling self-organization of institutions
• Discussion
Common Pool Resources
• Are used by multiple-users
• For which joint use involves subtractability,
that is, use by one user will subtract benefits
from another user’s enjoyment of the
resource
• It is difficult to exclude users
Management of CPRs
• Economic Theory predicts Nash equilibrium
and overharvesting
• Solutions to derive cooperative solution:
– Government will manage the resource
– A market will be created
• Laboratory experiments and field studies
show an alternative: self-organization of
institutions.
Factors important for selforganization
• Type of communication
• Building up mutual trust relationships
• Rules how to monitor and sanction defined
by the local users and implemented by local
users
• Memory of successful solutions by taboos,
rituals, religions, etc.
Immune System
• Distributed system which is able to detect
and eliminate invasions of pathogens.
• Detection: self vs non-self
• Response: generation antibodies
• Memory: storing successful responses
Pathogens
•
•
•
•
Bacteria
Parasites
Viruses
Fungi
Detection
Recognition
Response
- Continue generation of new cells.
- Replication of cells which bind lots
of pathogens: Antibodies
- Antibodies neutralize pathogens
Impact of Memory
Artificial Immune Systems
• Distributed systems for information
processes.
• Origin:
– study of immune systems
– bio-algorithms:
• genetic algorithms
• neural networks
Language development
• Different perspectives on language.
• Universal grammar/language:
• Genetic transmission
• Localized hard-wired neurological structures:
crickets and songbirds
• Higher animals learn language gradually: training
parameters of neural network
Complex adaptive system
approach
• Language:
–
–
–
–
result of local interactions of language users
self-organizing process
agents benefit from being understood (fitness)
clustering of agent with same language/dialect
Methodology
• Games:
– game theory for institutions, repeated games
with prisoners dilemma
– language games, imitation games
– evolution of grammar: fitness related to mutual
understanding
Vowels
Emergence of vowels by adaptive imitation games
(De Boer, 2000)
Methodology (II)
• Networks:
– Neural networks: learning by finding the right
connection strengths
– Immune networks: maintaining immune
memory, spreading information over other parts
of the network.
– Social networks.
Methodology (III)
• Evolutionary Computation
– Genetic and evolutionary algorithms:
•
•
•
•
fitness
selection
mutation
(cross-over)
Modeling self-organization of
institutions
•
•
•
•
Coding rules
Creating rules
Selecting rules
Remembering rules
Coding rules
• Grammar of Institutions (Crawford and
Ostrom, 1995)
• Rules are build up from 5 components:
–
–
–
–
–
Attributes (characteristics of the agents)
Deontic: may/must/must not
Aim: action of the agent
Conditions: when, where and how
Or else: sanctions when not following a rule
Creation of Rules
• Mutations and cross-over
• Immune systems: constant generation of
new lymphocytes
• Language: interaction with other groups and
with new experiences:
– Computer led to new words (e-mail & internet)
and new meanings (windows & mouse)
– Social groups: jargon of scientists
Genetic Libraries
Selection of Rules
Rules:
Levels of
analysis:
Processes:
Constitutional
Collective
Constitutional Collective
choice
choice
Formulation Policy-making
Governance Management
Adjudication Adjudication
Modification
Operational
Operational
choice
Appropriation
Provision
Monitoring
Enforcement
Selection of rules (II)
•
•
•
•
Criteria for success
Social networks
Mutual trust relationships
Recognition of trustworthy others
(reputation, symbols, indirect reciprocity)
Remembering Rules
•
•
•
•
Law, universities, taboos, rituals, religions
Reinforcement and disturbances
Resilience
Redundancy
Coverage of antigen space by antibodies
Fitness versus redundancy
(Hightower et al, 1995)
Fitness related to redundancy
(Hightower et al, 1995)
Training the system
• Allow small disturbances to maintain
training of the strength of the network, the
diversity and functional redundancy
Discussion
• Empirical evidence for self-organization of
institutions.
• Formal models may help to explain
observations.
• But how to formally model how rules
emerge, get selected and be remembered?
Discussion (II)
• We may learn from similarities and
differences between institutions, immune
systems, and language development.
• Computational tools exists to simulate
immune systems and language development
• Toward computational laboratories for
social-ecological systems.