Goal Recognition Design - Survey

Abstract

<jats:p>Goal recognition is the task of recognizing the objective of agents based on online observations of their behavior. Goal recognition design (GRD), the focus of this survey, facilitates goal recognition by the analysis and redesign of goal recognition models. In a nutshell, given a model of a domain and a set of possible goals, a solution to a GRD problem determines: (1) to what extent do actions performed by an agent reveal the agent’s objective? and (2) what is the best way to modify the model so that the objective of an agent can be detected as early as possible? GRD answers these questions by offering a solution for assessing and minimizing the maximal progress of any agent before recognition is guaranteed. This approach is relevant to any domain in which efficient goal recognition is essential and in which the model can be redesigned. Applications include intrusion detection, assisted cognition, computer games, and human-robot collaboration. This survey presents the solutions developed for evaluation and optimization in the GRD context, a discussion on the use of GRD in a variety of real-world applications, and suggestions of possible future avenues of GRD research.</jats:p>

Goal Recognition Control under Network Interdiction Using a Privacy Information Metric

“…As for the observer, redesigning the environment will improve explainability of the actor's behavior. Many metrics have been proposed to redesign the environment, such as worst case distinctiveness (wcd) [3], expected-case distinctiveness (ecd) [47], all-goals wcd (wcd (ag) ) [47], and relative goal uncertainty (rgu) [35]. As for more general plan recognition design problem, the worst-case distinctiveness for plans (wcpd) measures the number of observations needed to unambiguously identify the agent's plan [43].…”

“…These metrics for GRD are mainly formulated to optimize the maximum number of observations, which are required to unambiguously infer the goal or plan of the agent [43]. Such as the wcd of a domain D is an upper bound of the action number that the actor can perform in a stable model, before selecting a distinctive path to reveal the goal [3]. In addition, the GRD problem can be reformulated into an optimization problem with some constraints: the cost of the cost-optimal plan to achieve each goal g ∈ G is the same before and after removing the subset of actions [48].…”

“…Goal reasoning as one variant is the process in which intelligent agents continually reason about the goals they are pursuing [2]. Goal recognition design has been proposed to redesign the environment to facilitate goal recognition offline [3]. As one sub-problem of PAIR (plan activity and intent recognition) [4], goal recognition has been successfully applied to various applications, such as human-machine interaction (HMI) in social settings (home, offices, and hospitals) [5], agent modeling [6], critical infrastructure protection (CIP) [7], and some military applications about reasoning the goals of the terrorists or opponents [2,8].…”

“…In this paper, we quantify the privacy information leakage of actions or states with a min-entropy information metric, which is tightly associated with the goal uncertainty and can be used to aid in recognizing the goals. Aiming at assisting the observer to control the goal recognition process, in this paper, we follow the multi-model models, such as share (reveal, signal) or hide information [28,29], delay predictability [34] or assist recognition [3], reduce or improve uncertainty [35], and define the goal recognition control (GRC) problem under network interdiction with a privacy information metric as InfoGRC. Here, the observer will reduce the goal uncertainty value through limiting the action space that an actor can perform under network interdiction, while the actor manages to delay the goal recognition process through adding the goal uncertainty value by performing abnormal actions.…”

“…Figure 5portrays two possible solutions for placing barriers or blocks to interdict the passage of the actor. The goal recognition design problem with two kinds of redesign (interdiction): the wcd value is 4 in (a), the wcd value is 0 in (b)[3]. (a) A GRD domain; (b) redesign with one block.…”