Inferring the eventual goal of a mobile agent from noisy observations of its trajectory is a fundamental estimation problem. We initiate the study of such intent inference using a variant of a Rao-Blackwellized Particle Filter (RBPF), subject to the assumption that the agent's intent manifests through closed-loop behavior with a state-of-the-art provable practical stability property. Leveraging the assumed closed-form agent dynamics, the RBPF analytically marginalizes the linear-Gaussian substructure and updates particle weights only, improving sample efficiency over a standard particle filter. Two difference estimators are introduced: a Gaussian mixture model using the RBPF weights and a reduced version confining the mixture to the effective sample. We quantify how well the adversary can recover the agent's intent using information-theoretic leakage metrics and provide computable lower bounds on the Kullback-Leibler (KL) divergence between the true intent distribution and RBPF estimates via Gaussian-mixture KL bounds. We also provide a bound on the difference in performance between the two estimators, highlighting the fact that the reduced estimator performs almost as well as the complete one. Experiments illustrate fast and accurate intent recovery for compliant agents, motivating future work on designing intent-obfuscating controllers.

Abstract--Partially Observable Markov Decision Processes (POMDPs) provide a structured framework for decision-making under uncertainty, but their application requires efficient belief updates. Sequential Importance Resampling Particle Filters (SIRPF), also known as Bootstrap Particle Filters, are commonly used as belief updaters in large approximate POMDP solvers, but they face challenges such as particle deprivation and high computational costs as the system's state dimension grows. To address these issues, this study introduces Rao-Blackwellized POMDP (RB-POMDP) approximate solvers and outlines generic methods to apply Rao-Blackwellization in both belief updates and online planning. POMCPOW (left) and RB-POMCPOW (right) Tree Structure Comparison. Moreover, as Partially Observable Markov Decision Processes (POMDPs) the system's effective dimension grows, a substantial increase are a powerful mathematical framework for modeling in the number of particles may be required to maintain decision-making under uncertainty where an agent operates performance, resulting in high computational costs (e.g. Rao-Blackwellized Particle Filtering (RBPF) offer a promising POMDPs have been widely applied to various domains such solution to address some of these limitations of the SIRPF.

Autonomous underwater vehicles (AUVs) are becoming standard tools for underwater exploration and seabed mapping in both scientific and industrial applications \cite{graham2022rapid, stenius2022system}. Their capacity to dive untethered allows them to reach areas inaccessible to surface vessels and to collect data more closely to the seafloor, regardless of the water depth. However, their navigation autonomy remains bounded by the accuracy of their dead reckoning (DR) estimate of their global position, severely limited in the absence of a priori maps of the area and GPS signal. Global localization systems equivalent to the later exists for the underwater domain, such as LBL or USBL. However they involve expensive external infrastructure and their reliability decreases with the distance to the AUV, making them unsuitable for deep sea surveys.

… television network of 7,5000 cameras in the capital is expected to facilitate face-recognition technology and machine-learning-based video monitoring.

The Royal Bahamas Police Force (RBPF) could be on the verge of making another leap in the fight against crime in The Bahamas, with high-level meetings taking place this week with potential vendors and stakeholders in public safety artificial intelligence technology. During a welcome and oath-swearing ceremony for nearly 100 new police recruits, Commissioner of Police Paul Rolle told the men and women that his executive team was present with the exceptions of two assistant commissioner's, including Assistant Commissioner Zhavargo Dames, "who's representing me in another meeting trying to get some technology, additional technology for the Royal Bahamas Police Force". When contacted for specifics, Rolle told Eyewitness News: "We are doing some exploration with artificial intelligence." He did not expound on what area the AI technology could be used in or what it could potentially achieve in its use in The Bahamas. The use of AI in law enforcement is not uncommon in other jurisdictions with significant advances in recent years.