7 papers
Learning Markov Processes as Sum-of-Square Forms for Analytical Belief Propagation
Peter Amorese, Morteza Lahijanian
Harnessing the predictive capability of Markov process models requires propagating probability density functions (beliefs) through the model. For many existing models however, beli…
Learning Nonlinear Continuous-Time Systems for Formal Uncertainty Propagation and Probabilistic Evaluation
Peter Amorese, Morteza Lahijanian
Nonlinear ordinary differential equations (ODEs) are powerful tools for modeling real-world dynamical systems. However, propagating initial state uncertainty through nonlinear dyna…
Universal Learning of Stochastic Dynamics for Exact Belief Propagation using Bernstein Normalizing Flows
Peter Amorese, Morteza Lahijanian
Predicting the distribution of future states in a stochastic system, known as belief propagation, is fundamental to reasoning under uncertainty. However, nonlinear dynamics often m…
On Polynomial Stochastic Barrier Functions: Bernstein Versus Sum-of-Squares
Peter Amorese, Morteza Lahijanian
Stochastic Barrier Functions (SBFs) certify the safety of stochastic systems by formulating a functional optimization problem, which state-of-the-art methods solve using Sum-of-Squ…
Online Pareto-Optimal Decision-Making for Complex Tasks using Active Inference
Peter Amorese, Shohei Wakayama, Nisar Ahmed +1
When a robot autonomously performs a complex task, it frequently must balance competing objectives while maintaining safety. This becomes more difficult in uncertain environments w…
Optimal Cost-Preference Trade-off Planning with Multiple Temporal Tasks
Peter Amorese, Morteza Lahijanian
Autonomous robots are increasingly utilized in realistic scenarios with multiple complex tasks. In these scenarios, there may be a preferred way of completing all of the given task…
Let's Collaborate: Regret-based Reactive Synthesis for Robotic Manipulation
Karan Muvvala, Peter Amorese, Morteza Lahijanian
As robots gain capabilities to enter our human-centric world, they require formalism and algorithms that enable smart and efficient interactions. This is challenging, especially fo…