multi-agent simulation

**Multi-Agent Simulation** in semiconductor manufacturing is a **modeling approach where multiple autonomous agents (representing tools, lots, operators, transporters) interact according to defined rules** — the emergent behavior of the system reveals complex dynamics that cannot be predicted from individual agent behavior alone. **Key Agents in Fab Simulation** - **Tool Agents**: Model equipment availability, processing rules, PM schedules, and failures. - **Lot Agents**: Carry route information, priority, and processing history. - **Transport Agents**: Model AMHS (Automated Material Handling System) vehicle routing and delivery. - **Operator Agents**: Model human resource availability and task allocation. **Why It Matters** - **Emergent Behavior**: Complex fab phenomena (congestion, starvation, deadlocks) emerge naturally from agent interactions. - **Decentralized Control**: Test distributed decision-making strategies (like real fabs) rather than centralized optimization. - **Scalability**: Adding new tools, routes, or products just means adding new agents. **Multi-Agent Simulation** is **the fab as a society of agents** — modeling complex factory dynamics through the interactions of autonomous tool, lot, and transport agents.