Indirect Reciprocity

Status

Python-backed. This page describes the moran_models/nowak_mechanisms/indirect_reciprocity/ package in the sibling EvolvedCooperation repository. It is not yet a browser replay case study.

Indirect reciprocity is cooperation sustained by reputation. Rather than requiring repeated encounters with the same individual, an agent helps others whose public reputation signals that they are good cooperators — "I help you because others are watching."

How It Is Implemented Here

Each site carries a public reputation score. The positive routing kernel is biased toward higher-reputation recipients:

K^+_{j \to i} \propto \text{bias} + \text{reputation}_i^{\,\text{exponent}}

with row normalization applied afterward. After each step, the reputation of surviving sites is updated from observed helping output:

\text{rep}_i \leftarrow (1 - \omega) \times \text{rep}_{\text{parent}} + \omega \times \frac{B^+_{\text{parent}}}{\text{B\_plus\_scale}}

where $\omega$ is the observation weight. Agents that help more accumulate higher reputation, which causes them to receive more routed benefit — sustaining cooperation through the public reputation channel.

Key Parameters

Parameter	Default	Role
`reputation_default`	`0.5`	Initial reputation for all sites
`reputation_observation_weight`	`0.35`	How quickly reputation tracks recent helping
`reputation_kernel_bias`	`0.10`	Minimum routing weight regardless of reputation
`reputation_kernel_exponent`	`1.0`	Curvature of reputation-to-weight mapping
`B_plus_scale`	`1.0`	Scales cooperative benefit produced per unit trait
`C_scale`	`0.2`	Private cost per unit trait

Python Module Layout

moran_models/nowak_mechanisms/indirect_reciprocity/
  __init__.py
  indirect_reciprocity_model.py
  indirect_reciprocity_pygame_ui.py
  config/
    indirect_reciprocity_config.py

Usage

./.conda/bin/python -m moran_models.nowak_mechanisms.indirect_reciprocity.indirect_reciprocity_model

Live viewer:

./.conda/bin/python -m moran_models.nowak_mechanisms.indirect_reciprocity.indirect_reciprocity_pygame_ui

References

Nowak, M. A., & Sigmund, K. (1998). Evolution of indirect reciprocity by image scoring. Nature, 393, 573–577. https://doi.org/10.1038/31225
Nowak, M. A. (2006). Five rules for the evolution of cooperation. Science, 314(5805), 1560–1563. https://doi.org/10.1126/science.1133755

Status​

How It Is Implemented Here​

Key Parameters​

Python Module Layout​

Usage​

References​