Bernd Schattenberg

Planning agents in JAMES

Testing is an obligatory step in developing multiagent systems. For testing multiagent systems in virtual, dynamic environments, simulation systems are required that support a modular, declarative construction of experimental frames, that facilitate the embedding of a variety of agent architectures and that allow an efficient parallel, distributed execution. We introduce the system JAMES (a Java based agent modeling environment for simulation). In JAMES, agents and their dynamic environment are modeled as reflective, time-triggered state automata. Its possibilities to compose experimental frames based on predefined components, to express temporal interdependencies, to capture the phenomenon of proactiveness and reflectivity of agents are illuminated by experiments with planning agents. The underlying planning system is a general-purpose system, about which no empirical results exist besides traditional static benchmark tests. We analyze the interplay between heuristics for selecting goals, viewing range, commitment strategies, explorativeness, and trust in the persistence of the world and uncover properties of the the agent, the planning engine, and the chosen test scenario: TILEWORLD.

Advanced user assistance based on AI planning

Artificial Intelligence technologies enable the implementation of cognitive systems with advanced planning and reasoning capabilities. This article presents an approach to use hybrid planning - a method that combines reasoning about procedural knowledge and causalities - to provide user-centered assistance. Based on a completely declarative description of actions, tasks, and solution methods, hybrid planning allows for the generation of knowledge-rich plans of action. The information those plans comprise includes causal dependencies between actions on both abstract and primitive levels as well as information about their hierarchical and temporal relationships. We present the hybrid planning approach in detail and show its potential by describing the realization of various assistance functionalities based on complex cognitive processes like the generation, repair, and explanation of plans. Advanced user assistance is demonstrated by means of a practical application scenario where an innovative electronic support mechanism helps a user to operate a complex mobile communication device.

Companion-Technology: Towards User- and Situation-Adaptive Functionality of Technical Systems

The properties of multimodality, individuality, adaptability, availability, cooperativeness and trustworthiness are at the focus of the investigation of Companion Systems. In this article, we describe the involved key components of such a system and the way they interact with each other. Along with the article comes a video, in which we demonstrate a fully functional prototypical implementation and explain the involved scientific contributions in a simplified manner. The realized technology considers the entire situation of the user and the environment in current and past states. The gained knowledge reflects the context of use and serves as basis for decision-making in the presented adaptive system.

Hybrid planning using flexible strategies

In this paper we present a highly modular planning system architecture. It is based on a proper formal account of hybrid planning, which allows for the formal definition of (flexible) planning strategies. Groups of modules for flaw detection and plan refinement provide the basic functionalities of a planning system. The concept of explicit strategy modules serves to formulate and implement strategies that orchestrate the basic modules. This way a variety of fixed plan generation procedures as well as novel flexible planning strategies can easily be implemented and evaluated. We present a number of such strategies and show some first comparative performance results.

Plan Repair in Hybrid Planning

We present a domain-independent approach to plan repair in a formal framework for hybrid planning. It exploits the generation process of the failed plan by retracting decisions that led to the failed plan fragments. They are selectively replaced by suitable alternatives, and the repaired plan is completed by following the previous generation process as close as possible. This way, a stable solution is obtained, i.e. a repair of the failed plan that causes minimal perturbation.

Hybrid planning and scheduling

Planning and scheduling (P&S) constitute fundamental cognitive capabilities for systems to reason about plans and their causal structure. They are essential for producing a goal-oriented system behavior and supporting a user’s decision making. While planning is the method of creating courses of action that achieve goals or perform tasks, scheduling assigns consistent allocations of time and resources to activities. ‘‘Hybrid planning’’ refers to a distinct paradigm, which integrates building plans based on the individual action’s causal structure with obtaining plans from iteratively implementing abstract actions by pre-defined partial solutions. Combined, hierarchical model aspects represent regular solutions provided by domain experts, while causality-based techniques complete underspecified procedures and address exceptional cases. Applications of the technology range from planning out disaster relief missions [4] to assessing cyber-security measures [7].

Landmarks in Hierarchical Planning

In this paper we introduce a novel landmark technique for hierarchical planning. Landmarks are abstract tasks that are mandatory. They have to be performed by any solution plan. Our technique relies on a landmark extraction procedure that pre-processes a given planning problem by systematically analyzing the ways in which relevant abstract tasks can be decomposed. We show how the landmark information is used to guide hierarchical planning and present some experimental results that give evidence for the considerable performance increase gained through our technique.

On the Construction and Evaluation of Flexible Plan-Refinement Strategies

This paper describes a system for the systematic construction and evaluation of planning strategies. It is based on a proper formal account of refinement planning and allows to decouple plan-deficiency detection, refinement computation, and search control. In adopting this methodology, planning strategies can be explicitly described and easily deployed in various system configurations. We introduce novel domain-independent planning strategies that are applicable to a wide range of planning capabilities and methods. These so-called HotSpotstrategies are guided by information about current plan defects and solution options. The results of a first empirical performance evaluation are presented in the context of hybrid planning.

A unifying framework for hybrid planning and scheduling

Many real-world application domains that demand planning and scheduling support do not allow for a clear separation of these capabilities.Typically, an adequate mixture of both methodologies is required, since some aspects of the underlying planning problem imply consequences on the scheduling part and vice versa. Several integration efforts have been undertaken to couple planning and scheduling methods, most of them using separate planning and scheduling components which iteratively exchange partial solutions until both agree on a result. This paper presents a framework that provides a uniform integration of hybrid planning-the combination of operator based partial order planning and abstraction based hierarchical task network planning-and a hierarchical scheduling approach. It is based on a proper formal account of refinement planning, which allows for the formal definition of hybrid planning, scheduling, and search strategies. In a first step, the scheduling functionality is used to produce plans that comply with time restrictions and resource bounds. We show how the resulting framework is thereby able to perform novel kinds of search strategies that opportunistically interleave what used to be separate planning and scheduling processes.

Companion-Technology: An Overview

Companion-technology is an emerging field of cross-disciplinary research. It aims at developing technical systems that appear as “Companions” to their users. They serve as co-operative agents assisting in particular tasks or, in a more general sense, even give companionship to humans. Overall, Companion-technology enables technical systems to smartly adapt their services to individual users’ current needs, their requests, situation, and emotion. We give an introduction to the field, discuss the most relevant application areas that will benefit from its developments, and review the related research projects.