Agent Core

An Agent Core is an agentic ai system architecture component that serves as the central coordination hub for decision processing and component orchestration within an agentic ai system architecture.

• AKA: Agent Central Controller, Agent Coordination Hub.
• Context:
  • It can typically orchestrate Agent Core Request Processing from agent core user input to agent core system response.
  • It can typically coordinate Agent Core Component Communication between agent core planning modules, agent core memory modules, and agent core tool modules.
  • It can typically manage Agent Core Control Flow through agent core sequential processing and agent core parallel coordination.
  • It can typically implement Agent Core Response Generation by synthesizing agent core component outputs.
  • It can often integrate with agent core external systems through agent core api interfaces.
  • It can often maintain Agent Core State Management across agent core multi-turn interactions.
  • It can range from being a Simple Agent Core to being a Complex Agent Core, depending on its agent core coordination complexity.
  • It can range from being a Centralized Agent Core to being a Distributed Agent Core, depending on its agent core processing architecture.
  • ...
• Examples:
  • Agent Core Processing Patterns, such as:
    • Agent Core Sequential Processing Pattern implementing agent core linear workflows.
    • Agent Core Hub Pattern centralizing agent core component communication.
    • Agent Core Pipeline Pattern for agent core staged processing.
  • Agent Core Implementation Types, such as:
    • Agent Core LLM-Based Implementation using agent core language model orchestration.
    • Agent Core Rule-Based Implementation following agent core deterministic logic.
    • Agent Core Hybrid Implementation combining agent core multiple approaches.
  • Agent Core Architecture Variants, such as:
    • Agent Core Microservice Implementation for agent core distributed deployment.
    • Agent Core Monolithic Implementation for agent core single-process execution.
  • ...
• Counter-Examples:
  • Agentic System Planning Layer, which provides specific planning functionality rather than central coordination.
  • Multi-Agent System, which involves multiple autonomous agents rather than a single central processor.
  • Agent System Component, which represents individual functional units rather than the coordinating hub.
• See: Agentic AI System Architecture, Agent System Component, R-T-P-M Framework, LLM-based Agent System Architecture.

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