Goal recognition is the problem of inferring the (unobserved) goal of an agent, based on a sequence of its observed actions [4, 2, 1, 5]. It is a fundamental research problem in artificial intelligence, closely related to plan, activity, and intent recognition [10]. In offline recognition the entire sequence of observations is provided to the agent ahead of time. In contrast, in online recognit...

One drawback with using plan recognition in adversarial games is that often players must commit to a plan before it is possible to infer the opponent’s intentions. In such cases, it is valuable to couple plan recognition with plan repair, particularly in multi-agent domains where complete replanning is not computationally feasible. This paper presents a method for learning plan repair policies ...

In this paper, we propose a formal model of plan recognition for inclusion in a cognitive agent programming framework. The model is based on the Situation Calculus and the ConGolog agent programming language. This provides a very rich plan specification language. Our account also supports incremental recognition, where the set of matching plans is progressively filtered as more actions are obse...

|A novel task instruction method for future intelligent robots is presented. In our method, a robot learns reusable task plans by watching a human perform assembly tasks. Functional units and working algorithms for visual recognition and analysis of human action sequences are presented. The overall system is model based and integrated at the symbolic level. Temporal segmentation of a continuous...

Recognizing the mental-state, i.e., the beliefs, desires, plans, and intentions, of other agents situated in the environment is an important part of intelligent activity. Doing this with limited resources and in a continuously changing environment, where agents are continuously changing their mind, is a challenging task. In this paper, we provide algorithms for performing reactive plan recognit...

Abduction is widely used in the task of plan recognition, since it can be viewed as the task of finding the best explanation for a set of observations. The major drawback of abduction is its computational complexity. The task of abductive reasoning quickly becomes intractable as the background knowledge is increased. Recent efforts in the field of computational linguistics have enriched computa...

In our previous research, we investigated the properties of case-based plan recognition with incomplete plan libraries. Incremental construction of plan libraries along with retrieval based on similarities among planning situations (rather than on similarities among planning actions) enables recognition in light of novel planning actions. In this paper we investigate the recognition behavior in...

Intelligent help systems aim at providing optimal help to the users of complex application systems. In this context plan recognition is essential for a cooperative system behaviour in that it allows the prediction of future user actions, the ascertainment of suboptimal action sequences or even serves as a basis for user-adapted tutoring or learning components. In this paper a new approach to in...

This paper 1 describes the simulation of an attack recognition system in a distributed environment. The underlying technique of attack recognition is based on assertion checking. An auxiliary process called watchdog queries the users for a scope-le, from which an as-sertable plan called Sprint plan is generated. The sprint plan consists of carefully derived assertions, which forms the basis for...