agent-swarm-design

Blackboard architecture provides a shared state for loose coupling and effective coordination among specialized trading agents. Agents communicate by reading and writing to this central blackboard, ensuring robust system interaction.

Design multi-agent pipelines by creating simple, specialized, and skeptical agents with clear responsibilities. Define communication patterns and debate protocols via the blackboard read/write protocols, ensuring each agent handles its lifecycle and errors gracefully.

Common anti-patterns in swarm intelligence involve creating overly complex agents, lacking skepticism in decision-making, and failing to implement proper error handling. The framework provides guidance to avoid these coordination and reliability failures.

Inter-agent communication in a blackboard swarm architecture works through read and write protocols to a shared state. Agents do not communicate directly; instead, they post updates and retrieve information from the blackboard.

Integrating local AI models is required for reasoning within the multi-agent autonomous trading system. The agents rely on these models to process information, make decisions, and interact with the blackboard architecture.