4 papers · 1 filter
Active Perception with Initial-State Uncertainty: A Policy Gradient Method
Chongyang Shi, Shuo Han, Michael Dorothy +1
This paper studies the synthesis of an active perception policy that maximizes the information leakage of the initial state in a stochastic system modeled as a hidden Markov model…
Robust Reward Design for Markov Decision Processes
Shuo Wu, Haoxiang Ma, Jie Fu +1
The problem of reward design examines the interaction between a leader and a follower, where the leader aims to shape the follower's behavior to maximize the leader's payoff by mod…
Planning with Probabilistic Opacity and Transparency: A Computational Model of Opaque/Transparent Observations
Sumukha Udupa, Jie Fu
Qualitative opacity of a secret is a security property, which means that a system trajectory satisfying the secret is observation-equivalent to a trajectory violating the secret. I…
Information-Theoretic Opacity-Enforcement in Markov Decision Processes
Chongyang Shi, Yuheng Bu, Jie Fu
The paper studies information-theoretic opacity, an information-flow privacy property, in a setting involving two agents: A planning agent who controls a stochastic system and an o…