Markov Engine (IP-Restricted)

Submitted by Endarr Carlton… on

Markov Engine (IP-Restricted)

The Markov Engine is the internal transition core within the NashMark-AI architecture. It converts system events into state transitions and equilibrium signals. All weighting rules, coefficients, and transition parameters are IP-restricted. Only the external shell, required for reference and integration, is published.

IP-Restricted Component. All transition matrices, jurisdictional mappings, escalation thresholds and proportionality coefficients are withheld.

1. Position in the Architecture

  • Receives action traces and system events from NashMark-AI simulations.
  • Produces structured state transitions for downstream legal engines.
  • Feeds Sansana / PHM, Sentinel, BCE and EEE with volatility and drift signals.
  • Provides equilibrium and risk indicators to the broader governance layer.

2. Mathematical Shell (Public)

$ S = \{ s_0, s_1, \dots, s_n \} $

$ P = [p_{ij}],\quad p_{ij} = \Pr(s_{t+1} = s_j \mid s_t = s_i) $

$ \pi_t = \pi_{t-1} P,\quad \pi_t \in \Delta^{n} $

  • $ S $ — abstract state space (dimensions withheld).
  • $ P $ — transition matrix (values withheld).
  • $ \pi_t $ — current system distribution.

3. Integration Contract

ChannelSymbolOutput
Input$ x_t $Aggregated event vector.
Input$ s_t $Current system state.
Output$ s_{t+1} $Next system state.
Output$ E_t $Equilibrium proximity signal.
Output$ V_t $Volatility index.
Output$ R_t $Risk tier for legal engines.

4. Public Pseudocode Shell


def markov_engine_step(state_t, event_vector):
    z = phi(event_vector)            # feature mapping (redacted)
    row = select_transition(state_t) # transition rule (redacted)
    next_state = transition(row)     # state update

    eq_signal = equilibrium(next_state) # equilibrium index (redacted)
    drift = drift_index(state_t, next_state)
    risk = classify(next_state)

    return next_state, eq_signal, drift, risk

5. Deployment Notes

  • Distributed only as a compiled module or through a secured API.
  • Transition matrices, coefficients, and harm-weight parameters are not public.
  • Legal engines use the outputs; internal logic is not exposed.
  • Research simulations use simplified matrices not suitable for governance.

© 2025 Truthfarian · Markov Engine · IP-Restricted Component