Partial Observability Amplification of Misalignment

Validate core concepts, establish baselines, and define technical requirements.

Steps

• Literature & Benchmark Survey(4 wks)
  Map state‑of‑the‑art credit‑assignment, belief‑based communication, and adversarial detection techniques.
• Formal Problem Definition(3 wks)
  Specify the Dec‑POMDP formulation, belief hierarchy, and misalignment metrics.
• Proof‑of‑Concept Simulations(4 wks)
  Implement lightweight agents in OpenAI Gym/SMAC to test belief‑divergence signals and reward decomposition.
• Feasibility Report & Technical Spec(2 wks)
  Document assumptions, risk assessment, and system architecture.

Milestones

Risks

• Inadequate benchmark coverage leading to blind spots
• Mis‑estimation of belief‑divergence impact on credit assignment

Build a modular BAAC prototype with core modules: belief hierarchy, dynamic communication, joint world model, and reward decomposition.

Steps

• Belief‑Aware Variational Encoder(6 wks)
  Implement multi‑scale belief encoder with KL‑regularized bottleneck.
• Dynamic Belief‑Driven Communication(6 wks)
  Design attention‑based token generator and decoder for belief divergence messages.
• Joint Belief‑World Model(8 wks)
  Train autoregressive transformer to predict next observation and belief vector.
• Misalignment‑Aware Reward Engine(4 wks)
  Integrate belief‑divergence penalty into PPO/COMA training loop.
• Adversarial Alignment Discriminator(4 wks)
  Train a lightweight LSTM‑CNN discriminator to flag abnormal belief trajectories.

Milestones

Risks

• Bottleneck capacity too low causing loss of task‑relevant info
• Communication latency exceeding real‑time constraints
• Adversarial discriminator over‑fitting to synthetic data

Dependencies

• Phase 1 Feasibility Report

Scale the prototype to heterogeneous agent teams, optimize communication bandwidth, and integrate with a distributed training framework.

Steps

• Hierarchical Policy Graph Construction(6 wks)
  Extend belief hierarchy to support macro‑actions and option discovery.
• Bandwidth‑Aware Message Scheduler(4 wks)
  Implement event‑triggered communication and adaptive compression.
• Distributed Training Pipeline(6 wks)
  Deploy on Ray/RLlib or Unity ML‑Agents for multi‑node scaling.
• Cross‑Domain Generalization Tests(4 wks)
  Validate performance on unseen SMAC maps and real‑world simulation environments.
• Safety & Compliance Review(2 wks)
  Conduct formal verification of misalignment detection logic and communication safety.

Milestones

Risks

• Scalability bottlenecks in belief aggregation
• Network congestion under high agent counts
• Distribution shift causing misalignment detector drift

Dependencies

• Phase 2 Core BAAC Prototype

Deploy the system in a controlled real‑world environment (e.g., UAV swarm or warehouse robots) and evaluate safety, robustness, and human‑in‑the‑loop oversight.

Steps

• Hardware‑Software Integration(6 wks)
  Map belief encoder to onboard sensors (LiDAR, camera, IMU) and integrate communication stack.
• Pilot Scenario Design(4 wks)
  Define mission profiles, safety constraints, and evaluation metrics.
• Field Trials(8 wks)
  Run 20+ mission cycles, collect telemetry, and monitor misalignment events.
• Human‑in‑the‑Loop Evaluation(4 wks)
  Provide interpretable belief divergence dashboards to operators and capture feedback.
• Compliance & Certification(2 wks)
  Prepare safety case and obtain relevant regulatory approvals.

Milestones

Risks

• Unforeseen sensor noise degrading belief estimates
• Communication latency spikes in real‑world networks
• Operator overload due to complex dashboards

Dependencies

• Phase 3 Scalable Multi‑Agent System

Finalize production‑grade codebase, automate scaling, and establish monitoring & maintenance pipelines.

Steps

• Codebase Refactoring & Documentation(4 wks)
  Ensure modularity, unit tests, and API stability for production use.
• Auto‑Scaling & Load Balancing(4 wks)
  Configure Kubernetes/Cloud Run for dynamic agent deployment.
• Continuous Monitoring & Alerting(2 wks)
  Implement dashboards for belief divergence, communication health, and safety events.
• Customer Onboarding & Training(2 wks)
  Create user guides, training modules, and support channels.

Milestones

Risks

• Deployment drift causing misalignment spikes
• Scaling limits under peak load
• Insufficient support documentation leading to user errors

Dependencies

• Phase 4 Real‑World Pilot Success