Agent Loops

An AGI doesn't just process static data; it is an Agent that acts on an environment. The "Agent Loop" is the continuous cycle that keeps the system alive and pursuing goals.

The Standard Cognitive Cycle

Most AGI architectures follow a variation of the Sense-Think-Act loop.

graph TD
    subgraph Environment
    E[World State]
    end
    
    E -->|Sense| P[Perception]
    P -->|Update| M[Internal Model / Memory]
    M -->|Plan| D[Decision Making / Reasoning]
    D -->|Act| A[Action/Effectors]
    A -->|Change| E
    
    D -.->|Meta-Reasoning| M

Components of the Loop

1. Sensing (Perception)

Converting raw signals (camera, sensors, text) into internal representations. In Hyperon, this means creating "Atoms" in the AtomSpace.

2. Understanding (Modeling)

Updating the internal world model based on new evidence. If a sensed "Object" isn't where it was expected to be, the model is updated to reflect the new position.

3. Deliberation (Planning)

Searching through possible actions to find the one that best satisfies current goals. This uses the Reasoning Engines.

4. Action (Effection)

Sending commands to actuators (robot arms, web browsers, or text generators).

Real-Time Constraints

In a true AGI, this loop must run at different speeds:

• Reactive Loop: Milliseconds (e.g., pulling a hand away from fire).
• Deliberative Loop: Seconds/Minutes (e.g., planning a route).
• Reflective Loop: Hours/Days (e.g., analyzing past performance to improve).

Goal-Driven Autonomy

Unlike a chatbot that waits for a prompt, a goal-driven agent loop is always running. If there is no immediate task, the "Goal Manager" might trigger Curiosity—an internal goal to explore the environment or organize its own memory to be more efficient in the future.

Next: Hyperon section