This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning

things. For example, we can drive to dinner while conversing in depth with a visiting scholar, or we can make coffee while planning dessert. However, these benefits may be offset by costs. The automatic pilot can lead us astray, caus-ing errors and sometimes catastrophes (Reason & Myceilska, 1982

We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts

Active networks allow their users to inject customized programs into the nodes of the network. An extreme case, in which we are most interested, replaces packets with "capsules" -- program fragments that are executed at each network router/switch they traverse. Active architectures permit a massive increase in the sophistication of the computation that is performed within the network. They will enable new applications, especially those based on application-specific multicast, information fusion, and other services that leverage network-based computation and storage. Furthermore, they will accelerate the pace of innovation by decoupling network services from the underlying hardware and allowing new services to be loaded into the infrastructure on demand. In this paper, we describe our vision of an active network architecture, outline our approach to its design, and survey the technologies that can be brought to bear on its implementation. We propose that the research community mount a j...

Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empirically compare the eight models and their extensions, (3

Abstract. We present a prototypical system, plasp, implementing Planning by compilation to Answer Set Programming (ASP). Our approach is inspired by Planning as Satisfiability, yet it aims at keeping the actual compilation simple in favor of modeling planning techniques by meta-programming in ASP

The semantic structure of texts can be described both at the local microlevel and at a more global macrolevel. A model for text comprehension based on this notion accounts for the formation of a coherent semantic text base in terms of a cyclical process constrained by limitations of working memory. Furthermore, the model includes macro-operators, whose purpose is to reduce the information in a text base to its gist, that is, the theoretical macrostructure. These opera-tions are under the control of a schema, which is a theoretical formulation of the comprehender's goals. The macroprocesses are predictable only when the control schema can be made explicit. On the production side, the model is con-cerned with the generation of recall and summarization protocols. This process is partly reproductive and partly constructive, involving the inverse operation of the macro-operators. The model is applied to a paragraph from a psycho-logical research report, and methods for the empirical testing of the model are developed. The main goal of this article is to describe the system of mental operations that underlie the processes occurring in text comprehension and in the production of recall and summariza-tion protocols. A processing model will be outlined that specifies three sets of operations. First, the meaning elements of a text become

Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI planning, decision analysis, operations research, control theory and economics. While the assumptions

In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling

A new motion planning method for robots in static workspaces is presented. This method proceeds in two phases: a learning phase and a query phase. In the learning phase, a probabilistic roadmap is constructed and stored as a graph whose nodes correspond to collision-free configurations and whose