Dual-layer coordination framework for urban mining: Integration of social network analysis and multi-agent systems

Area of Science:

• Environmental Science
• Resource Management
• Complex Systems

Background:

• Urban mining involves multiple independent agents across supply, recycling, reuse, and regulation.
• Coordination challenges arise from diverse agent interests and interactions.
• Effective multi-agent systems are crucial for sustainable urban resource recovery.

Purpose of the Study:

• To examine dual-layer coordination among four key urban mining agents.
• To analyze agent behaviors using multi-period game theory and a heterogeneous social network model.
• To evaluate policy impacts on cooperation and collaboration in urban mining.

Main Methods:

• Integrated multi-agent based simulation (MABS) with game theory and social network models.
• Simulated agent interactions and feedback loops across multiple periods.
• Analyzed various policy scenarios, including price schemes and subsidy mechanisms.

Main Results:

• Non-cooperative strategies are prevalent, but price adjustments can foster cooperation in recycling and sorting.
• Gradual subsidy phase-outs stabilize collaboration; technical subsidies drive reuse agent innovation.
• Network effects require careful tuning; smaller agent groups exhibit better coordination.

Conclusions:

• Policy interventions, particularly price adjustments and phased subsidies, can significantly improve urban mining collaboration.
• Agent interactions and network structures critically influence cooperative outcomes.
• Findings provide a foundation for optimizing urban mining systems and policy-making.