Stochastic Goal Recognition Design

Authors

  • Christabel Wayllace Washington University in St. Louis

DOI:

https://doi.org/10.1609/aaai.v33i01.33019904

Abstract

Given an environment and a set of allowed modifications, the task of goal recognition design (GRD) is to select a valid set of modifications that minimizes the maximal number of steps an agent can take before its goal is revealed to an observer. This document presents an extension of GRD to the stochastic domain: the Stochastic Goal Recognition Design (S-GRD). The GRD framework aims to consider: (1) Stochastic agent action outcomes; (2) Partial observability of agent states and actions; and (3) Suboptimal agents. In this abstract we present the progress made towards the final objective as well as a timeline of projected conclusion.

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Published

2019-07-17

How to Cite

Wayllace, C. (2019). Stochastic Goal Recognition Design. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9904-9905. https://doi.org/10.1609/aaai.v33i01.33019904

Issue

Section

Doctoral Consortium Track