TSP Accepted

I am glad to announce that our paper Inverse Filtering for Hidden Markov Models with Applications to Counter-Adversarial Autonomous Systems (an updated version is available in Chapter 7 of my thesis) has been accepted for publication in the IEEE Transactions on Signal Processing.

In this work, we formulate and propose solutions to the problem of inverse dynamical Bayesian inference (filtering) for hidden Markov models. In other words, given a sequence of posteriors, we present identifiability results together with a method to identify the filter’s parameters, comprising the transition matrix of the hidden process, the matrix of observation likelihoods as well as the sequence of measured observations y₁, …, y_N.

As an application of our results, we demonstrate the design of a counter-adversarial autonomous system: How can we estimate the accuracy of an adversary’s sensor, based on measurements of its actions? We believe that this paper significantly advances the toolset available to practitioners dealing with counter-adversarial systems.

The work has been developed in collaboration with Cristian Rojas, Vikram Krishnamurthy and Bo Wahlberg. We are very excited about this line of research – let us know if you have any comments!