Deliberation

How It Works

The Deliberation Transcript

Each deliberation cycle produces a transcript entry pairing the agent's reasoning with the bio-system response it triggered. The full transcript accumulates across cycles so the LLM in cycle 3 sees cycles 1 and 2.

=== Your inner deliberation (private — not speech) ===

[Cycle 1]
You thought: The guard is sleeping and I notice keys on his belt.
I could try to take them, but that risks waking him...
Your experience responded:
- Memory: Last time you reached for something near a sleeping NPC,
  the noise check succeeded (salience=0.71)
- Prediction: stealth actions near sleeping entities have 72% success rate

[Cycle 2]
You thought: Given the memory of success with stealth near sleeping
NPCs, and the prediction of 72% success, I'll reach for the keys slowly...
Your experience responded:
- Memory: Slow movements reduce noise check difficulty by one tier
- Prediction: combined stealth + slow movement → 89% success estimate

The transcript uses a proportional token budget: min(2000, available × 0.3). On 4K local models this gives ~891 tokens; on 8K+ models it caps at 2000. Oldest entries are dropped first when the budget is exceeded.

Computed Salience

Each thought receives a computed salience score (0.0–1.0) based on how strongly the bio-systems responded to it.

The top_by_salience query on WorkingMemorySet returns the highest-salience thoughts first, so the most important reasoning surfaces in the prompt when token budget is tight.

The Thinking Panel

In interactive mode, the thinking panel shows a continuous stream of the agent's inner thoughts across the entire session.

Cycle 1/3  8.2s  enriched: hippocampus, nac
I notice the dragon is approaching from the east. My memory
recalls that fire dragons are vulnerable to water attacks.
—— hippocampus, nac s=0.69
Given my earlier success with the water spell, I should try
to find the river to the north before engaging directly.
—— hippocampus s=0.54
The villagers mentioned a well near the town square. I recall
wells can be used as water sources too — closer than the river.

Inner Monologue

Deliberation reasoning is framed as private inner thought. The agent thinks to itself in first person and explores autonomously before seeking user input.

ThoughtGate

A composite gate that decides whether the agent should deliberate on the current working memory state.

Short-circuit cascade:
1. Refractory    — don't re-fire within 2 ticks of last pass
2. Energy        — don't think below 15% of token budget
3. Salience      — score working memory head via SalienceScorer
4. Threshold     — score vs adaptive threshold (learns from outcomes)

The adaptive threshold adjusts based on whether past deliberations were useful — if thinking led to better actions, the threshold lowers (think more); if thinking was wasted, the threshold rises (act faster).

Entity Discovery

The agent discovers its world through three complementary tools:

Bio-Plausible Design

Architecture

ThoughtGate.should_think()
  ↓  (refractory → energy → salience → adaptive threshold)
BioEnrichmentPipeline.enrich(percept_text)
  ↓  (hippocampus, NAc, EC, cerebellum, SCN)
_compute_thought_salience(sections, memories, jaccard)
  ↓
WMS.add(THOUGHT, salience=computed)
  ↓
LLM prompt ← deliberation transcript + enrichment
  ↓
LLM response: {ready_to_act, action, reasoning}
  ↓
  ready_to_act=true → execute action
  ready_to_act=false → feed reasoning back → cycle 2+