Integrate Cognitive Mesh for threat reasoning and multi-site coordination

[JustAGhosT]

Context

PhoenixRooivalk (SkySnare/AeroNet) is a counter-UAS (drone defense) system with 27 defined agents and edge AI capabilities. With 685+ issues spanning phased hardware/software development and a Tier 1b score of 4.0, this is one of the most mature integration candidates in the Cognitive Mesh ecosystem. The existing multi-agent architecture maps directly onto CM's AgencyLayer, while the safety-critical nature of drone defense demands CM's ethical reasoning framework.

CM Source Issue: phoenixvc/cognitive-mesh#297

Integration Scope

Current AI Architecture

• 27 agents defined across detection, tracking, classification, and response phases
• Edge AI for real-time processing at deployment sites
• Multi-phase development with hardware/software co-evolution

What Needs to Happen

Integration Area	Details
Multi-Agent Orchestration	Connect 27 agents to CM AgencyLayer's MultiAgentOrchestrationEngine — coordinate detection-to-response pipeline with checkpointing and crash recovery via DurableWorkflowEngine
Threat Reasoning	Add threat classification via CM ReasoningLayer's DebateReasoningEngine — multiple reasoning agents debate threat classification (friend/foe, threat level, intent) to reach consensus before response escalation
Multi-Site Coordination	Implement cross-site threat correlation and resource sharing via CM AgencyLayer — coordinate detection across geographically distributed sensor arrays
Ethical AI for Use-of-Force	Integrate CM ethical reasoning framework (Brandom + Floridi) for autonomous response decisions — ensure proportional, accountable, and auditable use-of-force escalation

Agent Consolidation

Map the 27 existing agents to agentkit-forge configuration for standardized distribution:

• Detection agents (radar, RF, visual, acoustic) → sensor fusion agent group
• Tracking agents (trajectory, multi-target) → tracking coordination group
• Classification agents (friend/foe, type, intent) → threat assessment group
• Response agents (jamming, interception, alert) → response orchestration group

Each group maps to CM AgencyLayer patterns with well-defined ports and adapters.

Ethical AI Framework

CM ethical reasoning is critical for PhoenixRooivalk:

• Brandom's inferentialist framework — ensure threat response decisions follow from justified reasoning chains, not opaque model outputs
• Floridi's information ethics — evaluate proportionality, necessity, and accountability for each response action
• Reasoning transparency — full audit trail from detection through classification to response decision via CM MetacognitiveLayer's ReasoningTransparency

Next Steps

• Map 27 agents to CM AgencyLayer patterns — define ports, adapters, and orchestration topology for each agent group (detection, tracking, classification, response)
• Implement threat classification reasoning — build DebateReasoningEngine recipes for multi-agent threat consensus (friend/foe determination, threat level assessment, intent classification)
• Add ethical decision framework for autonomous responses — integrate Brandom + Floridi ethical reasoning into response escalation pipeline with full audit logging
• Design multi-site coordination protocol — implement cross-site agent communication via CM AgencyLayer for distributed threat correlation and coordinated response
• Configure agentkit-forge definitions — standardize all 27 agents into portable, versioned agent configurations

Related

Tracked in phoenixvc/cognitive-mesh#297 | Epic: phoenixvc/cognitive-mesh#305