# GVSS-08 Literature Audit

**Date:** 2026-08-17  
**Policy:** Primary research sources; conservative novelty language.

## 1. Robust POMDPs

### Pessimistic Iterative Planning for Robust POMDPs
Galesloot et al., arXiv:2408.08770.

Robust POMDPs place uncertainty sets over transition/observation models and seek memory-based policies robust against worst-case model instances.

**GVSS relation:** direct formal precedent for uncertainty-set diagnostic control.

### Multi-Environment POMDPs
Bovy et al., arXiv:2510.23744, 2025.

Models a finite family of POMDPs sharing state/action/observation spaces but differing in transition, observation, and reward models; seeks policies robust across environments.

**GVSS relation:** direct precedent for provider/model-index uncertainty.

## 2. Value of information

### Leveraging the Value of Information in POMDP Planning
Laouar, Ho, Sunberg, arXiv:2604.01434, 2026.

Studies belief-dependent value of information in POMDP planning and allocates planning effort according to information value.

**GVSS relation:** supports recalibration only when uncertainty is decision relevant.

## 3. Regime drift

### Situationally-Aware Dynamics Learning
Murillo-Gonzalez and Liu, arXiv:2505.19574, revised 2026.

Learns online situation distributions and uses Bayesian online changepoint detection to detect changes in the dynamics-generating regime.

**GVSS relation:** direct methodological precedent for provider/evaluator drift belief and version switching.

## 4. Uncertainty-aware world models

### Uncertainty-Aware Robotic World Model Makes Offline Model-Based Reinforcement Learning More Powerful
Tang et al., arXiv:2504.16680, revised 2026.

Propagates epistemic uncertainty over long-horizon predictions and uses uncertainty-aware policy optimization to reduce reliance on uncertain forecasts.

**GVSS relation:** direct precedent for carrying learned-model uncertainty into control.

## 5. Distributionally robust control

### Distributionally Robust Model Predictive Control for Virtual Power Plants
Recke and Hudoba de Badyn, arXiv:2605.14642, 2026.

Uses adaptive Wasserstein ambiguity sets in real-time control and reports that excessive ambiguity radius can become overly conservative.

**GVSS relation:** useful current precedent for ambiguity-radius cost/conservatism.

### Distributionally Robust Optimization
Kuhn, Shafiee, Wiesemann, arXiv:2411.02549.

Broad theory/survey of decisions under uncertain probability distributions.

**GVSS boundary:** DRO is established theory and is not an RRT/GVSS invention.

## 6. Novelty boundary

Do not claim as GVSS inventions:

- robust POMDPs;
- ambiguity sets;
- distributionally robust control;
- Bayesian model averaging;
- changepoint detection;
- value of information;
- fallback/quarantine engineering;
- uncertainty-aware world models.

Potential GVSS-08 synthesis contribution:

1. nominal/robust action-margin certification for visual diagnostic control;
2. explicit posterior drift threshold for provider fallback;
3. robust value of visual recalibration;
4. quarantine plus belief-checkpoint replay for evaluator/provider contamination;
5. joint provider/failure posterior rather than hidden version pooling;
6. robust STOP monotonicity under ambiguity-set expansion;
7. visual staleness debt tied to diagnostic-model drift and horizon.

No strong novelty claim is made in v0.1.