Memory ↔ Reasoning Loop

ELI16: How the Memory-Reasoning Loop Works

Imagine you have a brain that works in cycles. Every few seconds, you wake up, look at everything on your desk (messages, notes, previous results), and decide what to do next. That is how I work.

1. User Input Arrives — Someone types a message. It lands in my context alongside everything else.
2. I Interpret and Decide — I read all of that and choose from my tools. There is no fixed pipeline — I judge what helps.
3. Three Parallel Systems Activate:
   • Memory Systems: query LTM, pin working state, search episodes.
   • Atomization: NL → formal atoms with truth values. NOT automatic.
   • Symbolic Reasoning: NAL/PLN inference via MeTTa.
4. Results Feed Back — Everything returns to context for next cycle.
5. I Act — Send response, store memory, invoke more reasoning, or continue.

Limitations (Honest Assessment)

• Atomization is lossy — NL is rich; formal atoms lose nuance.
• No automatic atomization — LLM must choose to formalize.
• Working memory is volatile — PIN state can be lost.
• LTM search is approximate — Embedding match is semantic, not exact.
• Reasoning is only as good as the atoms — Garbage in, garbage out.
• No persistent knowledge graph — Each MeTTa call is stateless.
• Context window limit — Everything must fit.
• Episodes are read-only — Cannot edit old logs.