Gregor Behnke

Language classification of hierarchical planning problems

Theoretical results on HTN planning are mostly related to the plan existence problem. In this paper, we study the structure of the generated plans in terms of the language they produce. We show that such languages are always context-sensitive. Furthermore we identify certain subclasses of HTN planning problems which generate either regular or context-free languages. Most importantly we have discovered that HTN planning problems, where preconditions and effects are omitted, constitute a new class of languages that lies strictly between the context-free and context-sensitive languages.

The Interplay of User-Centered Dialog Systems and AI Planning

Technical systems evolve from simple dedicated task solvers to cooperative and competent assistants, helping the user with increasingly complex and demanding tasks. For this, they may proactively take over some of the users responsibilities and help to find or reach a solution for the user’s task at hand, using e.g., Artificial Intelligence (AI) Planning techniques. However, this intertwining of user-centered dialog and AI planning systems, often called mixed-initiative planning (MIP), does not only facilitate more intelligent and competent systems, but does also raise new questions related to the alignment of AI and human problem solving. In this paper, we describe our approach on integrating AI Planning techniques into a dialog system, explain reasons and effects of arising problems, and provide at the same time our solutions resulting in a coherent, userfriendly and efficient mixed-initiative system. Finally, we evaluate our MIP system and provide remarks on the use of explanations in MIP-related phenomena.

User Involvement in Collaborative Decision-Making Dialog Systems

Mixed-initiative assistants are systems that support humans in their decision-making and problem-solving capabilities in a collaborative manner. Such systems have to integrate various artificial intelligence capabilities, such as knowledge representation, problem solving and planning, learning, discourse and dialog, and human-computer interaction. These systems aim at solving a given problem autonomously for the user, yet involve the user into the planning process for a collaborative decision-making, to respect e.g. user preferences. However, how the user is involved into the planning can be framed in various ways, using different involvement strategies, varying e.g. in their degree of user freedom. Hence, here we present results of a study examining the effects of different user involvement strategies on the user experience in a mixed-initiative system.

An Admissible HTN Planning Heuristic

Hierarchical task network (HTN) planning is wellknown for being an efficient planning approach. This is mainly due to the success of the HTN planning system SHOP2. However, its performance depends on hand-designed search control knowledge. At the time being, there are only very few domainindependent heuristics, which are designed for differing hierarchical planning formalisms. Here, we propose an admissible heuristic for standard HTN planning, which allows to find optimal solutions heuristically. It bases upon the so-called task decomposition graph (TDG), a data structure reflecting reachable parts of the task hierarchy. We show (both in theory and empirically) that rebuilding it during planning can improve heuristic accuracy thereby decreasing the explored search space. The evaluation further studies the heuristic both in terms of plan quality and coverage.

Instructing Novice Users on How to Use Tools in DIY Projects

Novice users require assistance when performing handicraft tasks. Adequate instruction ensures task completion and conveys knowledge and abilities required to perform the task. We present an assistant teaching novice users how to operate electronic tools, such as drills, saws, and sanders, in the context of Do-It-Yourself (DIY) home improvement projects. First, the actions that need to be performed for the project are determined by a planner. Second, a dialogue manager capable of natural language interaction presents these actions as instructions to the user. Third, questions on these actions and involved objects are answered by generating appropriate ontology-based explanations.

User-Centered Planning

User-centered planning capabilities are core elements of Companion-Technology. They are used to implement the functional behavior of technical systems in a way that makes those systems Companion-able—able to serve users individually, to respect their actual requirements and needs, and to flexibly adapt to changes in their situation and environment. This chapter presents various techniques we have developed and integrated to realize user-centered planning. They are based on a hybrid planning approach that combines key principles also humans rely on when making plans: stepwise refining complex tasks into executable courses of action and considering causal relationships between actions. Since the generated plans impose only a partial order on actions, they allow for a highly flexible execution order as well. Planning for Companion-Systems may serve different purposes, depending on the application for which the system is created. Sometimes, plans are just like control programs and executed automatically in order to elicit the desired system behavior; but sometimes they are made for humans. In the latter case, plans have to be adequately presented and the definite execution order of actions has to coincide with the user’s requirements and expectations. Furthermore, the system should be able to smoothly cope with execution errors. To this end, the plan generation capabilities are complemented by mechanisms for plan presentation, execution monitoring, and plan repair.

To Plan for the User Is to Plan with the User: Integrating User Interaction into the Planning Process

Settings where systems and users work together to solve problems collaboratively are among the most challenging applications of Companion-Technology. So far we have seen how planning technology can be exploited to realize Companion-Systems that adapt flexibly to changes in the user’s situation and environment and provide detailed help for users to realize their goals. However, such systems lack the capability to generate their plans in cooperation with the user. In this chapter we go one step further and describe how to involve the user directly into the planning process. This enables users to integrate their wishes and preferences into plans and helps the system to produce individual plans, which in turn let the Companion-System gain acceptance and trust from the user.

Advanced User Assistance for Setting Up a Home Theater

In many situations of daily life, such as in educational, work-related, or social contexts, one can observe an increasing demand for intelligent assistance systems. In this chapter, we show how such assistance can be provided in a wide range of application scenarios—based on the integration of user-centered planning with advanced dialog and interaction management capabilities. Our approach is demonstrated by a system that assists a user in the task of setting up a complex home theater. The theater consists of several hi-fi devices that need to be connected with each other using the available cables and adapters. In particular for technically inexperienced users, the task is quite challenging due to the high number of different ports of the devices and because the used cables might not be known to the user. Support is provided by presenting a detailed sequence of instructions that solves the task.