no code implementations • 11 Dec 2023 • Subhajit Dutta Chowdhury, Zhiyu Ni, Qingyuan Peng, Souvik Kundu, Pierluigi Nuzzo
By iteratively applying ARGS to prune both the perturbed graph adjacency matrix and the GNN model weights, we can find adversarially robust graph lottery tickets that are highly sparse yet achieve competitive performance under different untargeted training-time structure attacks.
no code implementations • 16 Oct 2023 • Dengwang Tang, Rahul Jain, Ashutosh Nayyar, Pierluigi Nuzzo
We propose a Posterior Sampling-based reinforcement learning algorithm for POMDPs (PS4POMDPs), which is much simpler and more implementable compared to state-of-the-art optimism-based online learning algorithms for POMDPs.
no code implementations • 24 May 2023 • Krishna C. Kalagarla, Dhruva Kartik, Dongming Shen, Rahul Jain, Ashutosh Nayyar, Pierluigi Nuzzo
In this paper, we first introduce an optimal control theory for partially observable Markov decision processes (POMDPs) with finite linear temporal logic constraints.
no code implementations • 11 Apr 2023 • Kevin Chang, Nathan Dahlin, Rahul Jain, Pierluigi Nuzzo
Over the past decade, neural network (NN)-based controllers have demonstrated remarkable efficacy in a variety of decision-making tasks.
no code implementations • 2 Mar 2023 • Christopher Leet, Chanwook Oh, Michele Lora, Sven Koenig, Pierluigi Nuzzo
Given a list of products, the WSP amounts to finding a plan for a team of agents which brings every product on the list to a station within a given timeframe.
no code implementations • 27 Jan 2023 • Krishna C Kalagarla, Rahul Jain, Pierluigi Nuzzo
Constrained Markov decision processes (CMDPs) model scenarios of sequential decision making with multiple objectives that are increasingly important in many applications.
no code implementations • 15 Sep 2022 • Muhammad Waqas, Nikhil Vijay Naik, Petros Ioannou, Pierluigi Nuzzo
The STL predicates are then mapped to an aggregation of contracts associated with continuously differentiable time-varying control barrier functions.
no code implementations • 26 Mar 2022 • Muhammad Waqas, Muhammad Ali Murtaza, Pierluigi Nuzzo, Petros Ioannou
The safety-critical nature of adaptive cruise control (ACC) systems calls for systematic design procedures, e. g., based on formal methods or control barrier functions (CBFs), to provide strong guarantees of safety and performance under all driving conditions.
no code implementations • 17 Mar 2022 • Krishna C. Kalagarla, Dhruva Kartik, Dongming Shen, Rahul Jain, Ashutosh Nayyar, Pierluigi Nuzzo
Autonomous agents often operate in scenarios where the state is partially observed.
no code implementations • 1 Dec 2021 • Subhajit Dutta Chowdhury, Kaixin Yang, Pierluigi Nuzzo
Reverse engineering an integrated circuit netlist is a powerful tool to help detect malicious logic and counteract design piracy.
no code implementations • 27 Sep 2021 • Krishna C. Kalagarla, Rahul Jain, Pierluigi Nuzzo
We present a model-free reinforcement learning algorithm to find an optimal policy for a finite-horizon Markov decision process while guaranteeing a desired lower bound on the probability of satisfying a signal temporal logic (STL) specification.
no code implementations • 1 Nov 2020 • Krishna C. Kalagarla, Rahul Jain, Pierluigi Nuzzo
We present a method to find an optimal policy with respect to a reward function for a discounted Markov decision process under general linear temporal logic (LTL) specifications.
no code implementations • 28 Oct 2020 • Nathan Dahlin, Krishna Chaitanya Kalagarla, Nikhil Naik, Rahul Jain, Pierluigi Nuzzo
In an ever expanding set of research and application areas, deep neural networks (DNNs) set the bar for algorithm performance.
no code implementations • 23 Sep 2020 • Krishna C. Kalagarla, Rahul Jain, Pierluigi Nuzzo
Constrained Markov Decision Processes (CMDPs) formalize sequential decision-making problems whose objective is to minimize a cost function while satisfying constraints on various cost functions.