Reflective-Ethical Engine (REE)
REE is a cognitive architecture specification for agents that must act under uncertainty while affecting others.
The distinguishing requirement is moral continuity: an agent cannot discharge ethical responsibility by optimising it away. Even correct choices generate moral residue — persistent geometric cost that propagates forward and constrains future policy selection.
REE is not a moral rule engine. It does not assume ethical cost can be eliminated. It treats ethics as a structural constraint on the prediction-error minimisation loop, not as a separate module bolted on.
Latest result — 2026-04-03
EXQ-223 PASS: Minimal mind confirmed.
The REE core loop — E1 (associative world model) + E2 (fast transition predictor) + HippocampalModule (trajectory proposal) + go/no-go selection + raw harm/reward signals — produces stable navigation, harm avoidance, and resource acquisition without deliberation, goal evaluation, or commitment machinery. 3/3 criteria met across 3 independent seeds (harm_ratio 0.29–0.39; REE reward ~4.5× random).
The circuit topology of EXQ-223 matches the zebrafish larva (5–7 dpf) at the level of named structures. Dorsal pallium (E1) → cerebellum (E2) → lateral pallium (hippocampal module) → optic tectum + reticulospinal neurons (go/no-go) → lateral habenula (harm signal). The larva has no mature prefrontal cortex — no commitment architecture — which is exactly what the ablation removes. This is the only vertebrate for which the entire ~100,000-neuron CNS has been functionally imaged during behaviour (Ahrens et al., 2013, Nature Methods). The match was derived from functional-architecture arguments; it was not built to fit the biology.
→ Full analysis with circuit table and references
Where to start
| Document | What it covers |
|---|---|
| Architecture overview | The three irreducible functions (persistence, reachability, commitment) and how E1/E2/E3 implement them |
| Core invariants | Non-negotiable architectural constraints with claim IDs |
| Glossary | Canonical terminology — start here if terms are unfamiliar |
| Roadmap | Programme phases, phase-gate criteria, current status |
| Failure modes | What the architecture is designed to prevent and why |
Architecture
REE is organised into five computational components:
- E1 (Deep Predictor) — long-horizon recurrent context model; maintains world, self, and value across time
- E2 (Fast Predictor) — fast transition model
f(z_t, a_t) → z_{t+1}; operates on the conceptual sensorium (z_gamma / z_world), not raw sensory streams - L-space (Fused Manifold) — multi-depth latent state stratified by prediction horizon; z_self (motor-sensory, E2’s domain) and z_world (causal footprint, residue, E3’s domain)
- E3 (Trajectory Selector) — selects a coherent future trajectory by minimising reality cost, ethical cost, and residue curvature; includes hippocampal map, trajectory proposal, and commitment gating
- Hippocampal Systems — explicit multi-step rollouts and path memory; navigates residue-field terrain using E1 as associative prior
See the architecture section for detailed per-component documentation.
Claims and evidence
REE claims are typed (INV / ARC / MECH / Q / IMPL), registered with confidence scores, and governed through an experiment-evidence pipeline. Promotion and demotion decisions require experimental evidence from a real implementation substrate.
- Claims index — all registered claims with status and dependencies
- Conflicts — documented design tensions and their resolutions
- Governance state — promotion/demotion history
Implementation substrates
| Substrate | Status | Role |
|---|---|---|
| ree-v3 | Active development | Primary implementation target post-V2 hard stop |
| ree-v2 | Complete | Qualification lane; 15 experiments run (6 PASS / 7 FAIL) |
| ree-v1-minimal | Active (baseline) | Parity substrate |
The V2 experiment series triggered three hard-stop criteria, formalising the V3 transition. The core V3 design decisions are SD-004 (action objects as hippocampal map backbone), SD-005 (z_self/z_world latent split), and SD-006 (asynchronous multi-rate execution).
Contribute compute
REE experiments run on donated GPU and CPU time. If you have a machine with spare capacity, you can contribute in a few minutes — no account needed to get started, everything is open source.
Philosophical foundations
REE’s design is grounded in five axioms about the structure of ethical agency. See five axioms and the associated unpublished Synthese paper for the formal argument.