A Self-Policing Network
How incentive alignment leads participants to avoid dishonest regions of the graph, creating a self-policing network.
Participants prefer to transact with counterparties that are well connected to verified regions of the graph, because doing so increases their expected future rewards and reduces the risk of interacting with dishonest claimants.
Why this emerges under optimistic claims
Under optimistic diffusion claims:
- dishonest inflation can be challenged and punished via bond slashing
- disputed or low-quality interactions reduce edge weights (
) and future eligibility - policies can require higher bonds or stricter sampling for higher-risk regions
As a consequence, honest users learn to avoid transacting with nodes that are weakly connected to verified anchors or that frequently trigger disputes/challenges. This creates a self-reinforcing dynamic where honest regions deepen connectivity, while dishonest regions remain isolated and unprofitable.
The self-policing nature of the network not only maintains security but also reduces the costs associated with identifying malicious actors. The possibility of being challenged (and losing a bond) discourages dishonest behavior, while honest behavior compounds through connectivity and reputation.