DeepAI AI Chat
Log In Sign Up

Finding plans subject to stipulations on what information they divulge

by   Yulin Zhang, et al.

Motivated by applications where privacy is important, we consider planning problems for robots acting in the presence of an observer. We first formulate and then solve planning problems subject to stipulations on the information divulged during plan execution---the appropriate solution concept being both a plan and an information disclosure policy. We pose this class of problem under a worst-case model within the framework of procrustean graphs, formulating the disclosure policy as a particular type of map on edge labels. We devise algorithms that, given a planning problem supplemented with an information stipulation, can find a plan, associated disclosure policy, or both if some exists. Both the plan and associated disclosure policy may depend subtlety on additional information available to the observer, such as whether the observer knows the robot's plan (e.g., leaked via a side-channel). Our implementation finds a plan and a suitable disclosure policy, jointly, when any such pair exists, albeit for small problem instances.


page 1

page 2

page 3

page 4


What does my knowing your plans tell me?

For robots acting in the presence of observers, we examine the informati...

Phase Transitions of Plan Modification in Conformant Planning

We explore phase transitions of plan modification, which mainly focus on...

Plan Interdiction Games

We propose a framework for cyber risk assessment and mitigation which mo...

Design an IT Policy Implementation Plan

Information technology (IT) companies implement multi-dimensional policy...

Generalized Planning with Positive and Negative Examples

Generalized planning aims at computing an algorithm-like structure (gene...

The Limits of Learning and Planning: Minimal Sufficient Information Transition Systems

In this paper, we view a policy or plan as a transition system over a sp...

Case-Based Merging Techniques in OAKPLAN

Case-based planning can take advantage of former problem-solving experie...