Agent Coordination Patterns
Master how AI agents coordinate tasks, resolve conflicts, and achieve shared goals
Your Progress
0 / 5 completedHandling Agent Conflicts
In multi-agent systems, conflicts arise when agents compete for resources, have opposing goals, or attempt simultaneous operations. Effective conflict resolution prevents deadlocks, ensures fairness, and maintains system stability.
Interactive: Conflict Scenario Simulator
Explore different conflict types and resolution methods:
Resource Competition
Two agents need the same CPU resources simultaneously
Conflicting Agents:
🤖Agent A: ML Training
🤖Agent B: Real-time Processing
Resolution Process:
🚨
🚨 Conflict Detected
Step 1 of 4
Both agents request 80% CPU usage
Resolution Method:
Priority-Based
Outcome:
Critical task proceeds, others wait or use limited resources
🛠️ Resolution Methods
Priority-Based: Pre-defined rules determine winner
Negotiation: Agents communicate to find compromise
Arbitration: Third party makes binding decision
Locking: Serialize access to prevent conflicts