🤖 AI Summary
This work addresses the lack of standardized, auditable verification mechanisms for autonomous agents in regulated domains, where existing approaches either produce opaque conclusions or non-reproducible private logs. We propose a protocol-layer solution grounded in the four epistemic sources from Indian epistemology—perception, inference, analogy, and testimony—by encapsulating critical outputs as typed ClaimAttestations accompanied by deterministic or conditionally reproducible verify() operations, enabling offline auditability. We define the first cross-vendor reproducible wire format for claim verification and validate the protocol’s correctness and practicality through TLA+ formal modeling (covering 38,563 states with no invariant violations), a Python reference implementation passing 84 test cases, and LLM-based adjudicator experiments. Pilot results indicate that reference implementation quality significantly impacts false positive rates, with differences reaching up to 40 percentage points.
📝 Abstract
Autonomous agents deployed in regulated domains must produce a verification artifact per consequential output: a record an auditor can re-execute offline, capturing what was claimed, against what source, by whom, when, and how. Production verification today splits into two unstandardized halves. Probabilistic verdict patterns (self-consistency voting, reviewer LLM ensembles) produce judgments, not artifacts. Artifact-producing patterns (RAG, tool-augmented traces, generator-verifier loops) produce vendor-specific records no external auditor can reconstruct without bespoke integration.
Pramana defines the missing wire format. Every consequential agent output is wrapped in a typed ClaimAttestation with one of four variants (measurement, inference, analogy, citation), each paired with a verify() operation against the recorded source. verify() is deterministic for MeasurementClaim and CitationClaim. For InferenceClaim and AnalogyClaim, determinism is conditional on the oracle (audit-replayable when LLM-backed). The four-way typology derives from classical Indian epistemology (pramana, valid means of knowledge).
The lifecycle is specified in TLA+ and exhaustively verified under TLC across three symmetry-reduced models: 38,563 distinct reachable states, zero invariant violations. The Python reference implementation passes 84 tests. An A2A and MCP wire-extension manifest layers three deployment-grade invariants: reachability, SLA bound, and offline re-verifiability.
An exploratory pilot (n=100, 2,275 reviewer calls) probes LLM-as-judge in code generation. The strongest observation is a 40-percentage-point raw FPR delta across corpora, consistent with reference-solution quality contributing significantly. The pilot does not validate Pramana on its own; the structural argument and formal verification do that.