Day 2 – Conceptual Expansion
Date
20/05/2026
Focus
Formalizing autonomy architecture and research positioning.
Proposed Research Positioning
Empirical operationalization of autonomy calibration in smart-home AI.
Existing work focuses on:
- expectation management
- ethics
- trust calibration
- practitioner interpretation
Current work focuses on:
- operational autonomy
- intervention behavior
- reliability
- bounded execution
- measurable autonomy effects
Bounds
Tracked parameters:
- environment state
- device state
- autonomy configuration
- network condition
- user scenario
- intervention rule
- expected outcome
- observed outcome
- anomaly classification
Constraint: Performing actual Evaluation over feature expansion.
Autonomy Architecture
| Level | Model | Flow | Predictability |
|---|---|---|---|
| Low | Explicit rules | Fixed | High |
| Medium | Heuristic arbitration | Semi-dynamic | Moderate |
| High | Real-time inference/planning | Emergent | Variable |
Expanded Dimensions
| Dimension | Low | Medium | High |
|---|---|---|---|
| Initiative | Reactive | Context-triggered | Self-directed |
| Planning depth | Single-step | Multi-factor | Multi-stage |
| State awareness | Local | Contextual | Persistent |
| User confirmation | Frequent | Conditional | Sparse |
| Policy interpretation | Literal | Weighted | Abstract |
| Adaptation | None | Limited | Continuous |
| Execution flexibility | Fixed | Semi-variable | Emergent |
System Layers
Governance layer:
- policies
- bounds
- safety rails
Decision layer:
- deterministic execution
- heuristic arbitration
- agentic execution
Observability layer:
- telemetry
- intervention tracking
- rollback lineage
- execution tracing
Emerging Sketched Direction
Key concepts:
- bounded emergence
- calibrated autonomy
- execution entropy
- intervention elasticity
- policy-constrained autonomy
Potential future direction: Dynamic autonomy adaptation based on:
- intervention frequency
- uncertainty
- reliability degradation
- environmental ambiguity