50 citations · 125 across the 14 of their papers we have counts for
7 papers · 1 filter
Strategy Synthesis for Surveillance-Evasion Games with Learning-Enabled Visibility Optimization
Suda Bharadwaj, Louis Ly, Bo Wu +2
This paper studies a two-player game with a quantitative surveillance requirement on an adversarial target moving in a discrete state space and a secondary objective to maximize sh…
The Dirichlet Mechanism for Differential Privacy on the Unit Simplex
Parham Gohari, Bo Wu, Matthew Hale +1
As members of a network share more information with each other and network providers, sensitive data leakage raises privacy concerns. To address this need for a class of problems,…
Controller Synthesis for Multi-Agent Systems With Intermittent Communication: A Metric Temporal Logic Approach
Zhe Xu, Federico M. Zegers, Bo Wu +2
This paper develops a controller synthesis approach for a multi-agent system (MAS) with intermittent communication. We adopt a leader-follower scheme, where a mobile leader with ab…
Joint Inference of Reward Machines and Policies for Reinforcement Learning
Zhe Xu, Ivan Gavran, Yousef Ahmad +4
Incorporating high-level knowledge is an effective way to expedite reinforcement learning (RL), especially for complex tasks with sparse rewards. We investigate an RL problem where…
Control Theory Meets POMDPs: A Hybrid Systems Approach
Mohamadreza Ahmadi, Nils Jansen, Bo Wu +1
Partially observable Markov decision processes (POMDPs) provide a modeling framework for a variety of sequential decision making under uncertainty scenarios in artificial intellige…
Switched Linear Systems Meet Markov Decision Processes: Stability Guaranteed Policy Synthesis
Bo Wu, Murat Cubuktepe, Ufuk Topcu
Switched linear systems are time-varying nonlinear systems whose dynamics switch between different modes, where each mode corresponds to different linear dynamics. They arise natur…
Unpredictable Planning Under Partial Observability
Michael Hibbard, Yagiz Savas, Bo Wu +2
We study the problem of synthesizing a controller that maximizes the entropy of a partially observable Markov decision process (POMDP) subject to a constraint on the expected total…