Programming model for a bayesian neuromorphic compiler

A computer implemented method for performing probabilistic computations on mobile platform sensor data, the method comprising acts of:

• causing one or more processers to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of:
• translating a Bayesian model representing input mobile platform sensor data to a spiking neuronal network unit that implements the Bayesian model;
• using the spiking neuronal network unit, computing conditional probabilities for the input mobile platform sensor data, wherein the input mobile platform sensor data is a time series of vehicle error codes encoded as neuronal spikes;
• decoding the neuronal spikes, wherein the decoded neuronal spikes represent at least one mobile platform failure mode;
• and
• causing the mobile platform to initiate a mitigation action based on the at least one mobile platform failure mode.

A computer program product for performing probabilistic computations on mobile platform sensor data, the computer program product comprising:

• computer-readable instructions stored on a non-transitory computer-readable medium that are executable by a computer having one or more processors for causing the processor to perform operations of:
• translating a Bayesian model representing input mobile platform sensor data to a spiking neuronal network unit that implements the Bayesian model;
• using the spiking neuronal network unit, computing conditional probabilities for the input mobile platform sensor data, wherein the input mobile platform sensor data is a time series of mobile platform error codes encoded as neuronal spikes;
• decoding the neuronal spikes, wherein the decoded neuronal spikes represent at least one mobile platform failure mode;
• and
• causing the mobile platform to initiate a mitigation action based on the at least one mobile platform failure mode.