Benefits and Challenges of Multi-Agent Systems › Glossary
AI Agent HandbookAll chapters Benefits and Challenges of Multi-Agent Systems › GlossaryOne section · Sections in this chapter8 / 9 ↓
Coordination Overhead: The additional complexity and effort required to synchronize multiple agents, manage dependencies, and ensure they work together correctly without conflicts.
Deadlock: A situation where agents are stuck waiting for each other in a cycle, preventing any progress. For example, Agent A waits for Agent B, which waits for Agent C, which waits for Agent A.
Dependency Management: The practice of identifying which agents depend on outputs from other agents and ensuring they execute in the correct order to satisfy these dependencies.
Format Mismatch: A communication error where one agent sends data in a format (like plain text) that another agent cannot parse because it expects a different format (like JSON).
Graceful Degradation: The ability of a system to continue functioning, possibly with reduced capabilities, when one or more agents fail, rather than failing completely.
Modularity: The property of a system where components (agents) are independent and reusable, with clear interfaces that allow them to be combined in different ways.
Parallel Processing: The execution of multiple independent tasks simultaneously by different agents, resulting in faster overall completion than sequential execution.
Redundancy: Having multiple agents perform the same or similar tasks to provide verification, error checking, or backup capability, improving overall system reliability.
Shared State: Data or information that multiple agents need to access or modify, requiring synchronization mechanisms to prevent conflicts and ensure consistency.
Specialization: The practice of designing agents with focused expertise in specific domains or tasks, allowing each agent to perform better in its area than a generalist agent could.