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05241 Abstracts Collection Synthesis and Planning Dagstuhl Seminar Henry Kautz1, Wolfgang Thomas2 and Moshe Y. Vardi3 1 Univ. of Washington, US [email protected] 2 RWTH Aachen, DE [email protected] 3 Rice University, US [email protected] Abstract. From 12.06.05 to 17.06.2005 the Dagstuhl Seminar 05241 Synthesis and Planning was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The rst section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available. Keywords. AI planning, controller synthesis, partially observed do- mains, reactive computation, program analysis, games, model checking, satisability, Markov decision processes 05241 Executive Summary Synthesis and Planning This seminar has brought together researchers working in two complementary elds: automatic synthesis of (control) programs, and methods for devising plan- ning algorithms in artical intelligence (AI). This combines a strong thread of current research in automata theory with an area of possible but so far unex- plored applications. Keywords: Synthesis, planning Joint work of: Kautz, Henry; Thomas, Wolfgang; Vardi, Moshe Full Paper: http://drops.dagstuhl.de/opus/volltexte/2006/452 Dagstuhl Seminar Proceedings 05241 Synthesis and Planning http://drops.dagstuhl.de/opus/volltexte/2006/453 2 H. Kautz, W. Thomas and M. Y. Vardi Planning for Partially Observable, Non-Deterministic Domains Piergiorgio Bertoli (IRST - Trento, I) The problem of planning for partially observable, nondeterministic domains has lately attracted considerable interest, due to its relevance and complexity. It is relevant since it allows tackling the wide variety of realistic situations where only limited sensing is available, and where (some) actions may have uncertain outcomes. The problem has shown to be extremely complex, both theoretically and in practice, posing a serious scalability challenge. In this talk, I will present a general framework for partially observable plan- ning; in such framework, I will focus on describing a forward-chaining approach to the problem, and its implementation based on symbolic representation tech- niques; nally, I will draw relationships with other state-of-the-art approaches that tackle the same problem. Keywords: Planning, nondeterminism, partial observability External Exploration in Planning and Model Checking Practice Stefan Edelkamp (Universität Dortmund, D) Guided or heuristic search includes information on the distance to the set of terminal states into the exploration process and external search has shown to be important option to bypass limitations to main memory that are present when storing states for duplicate detection. The combination of both search approaches, denoted as External A*, is eective in solving challenging action planning and in model checking problems. The partition of sets of states into buckets indexed by the generating path costs and the heuristic estimates of the remaining costs reduces the number of external accesses to a theoretical optimum, namely to O(scan(v)+sort(e)) I/Os, where v and e are the vertices and edges of the explored state space subgraph. In the talk we further address how to integrate symbolic BDD-based representation especially for the automated generation of search heuristics. Keywords: Model checking, action planning, external search, symbolic search, automated heurstics, pattern databases, abstraction Synthesis and Planning 3 Analysis of Recursive Markov Chains, Recursive Markov Decision Processes, and Recursive Stochastic Games Kousha Etessami (University of Edinburgh, GB) Recursive Markov Chains (RMCs) ([Etessami-Yannakakis'05a]) are a natural abstract model of procedural probabilistic programs and related systems in- volving recursion and probability. RMCs dene a class of denumerable Markov chains with a rich theory generalizing that of multi-type Branching (stochas- tic) Processes and Stochastic Context-Free Grammars, and are intimately re- lated to probabilistic Pushdown Systems. Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs) extend RMCs with a controller and two adversarial players, respectively. In a series of recent papers with Mihalis Yannakakis, we have studied central algorithmic analysis and verication questions for RMCs, RMDPs, and RSSGs, providing some strong upper and lower bounds on the complexity of key algo- rithmic problems. In this talk I will provide a broad survey of this work, indicating some of the main techniques involved in our analyses. Joint work of: Kousha Etessami; Mihalis Yannakakis (Columbia U.) Keywords: Recursive Markov chains, rekursiv decision processes, recursive stochastig games Planning and Controller Synthesis for Hard Real-Time Robert P. Goldman (SIFT - Minneapolis, USA) Timed automata give a theoretical framework for controller synthesis and plan- ning for hard real-time systems. We are particularly interested in controller syn- thesis/planning for the case of closed-loop control over looping state spaces. We survey three approaches to timed automaton controller synthesis, an abstract symbolic framework [Asarin, Maler & Pneuli; Maler, Pneuli & Sifakis], a system based on graph search over time-abstract systems [Tripakis & Altisen], and a sys- tem based on articial intelligence planning [Musliner,Durfee & Shin; Goldman, Musliner & Pelican]. Even in these closely-related approaches, we see substantial dierences in framing assumptions that lead to quite dierent algorithms. Keywords: Planning, controller synthesis, real-time systems 4 H. Kautz, W. Thomas and M. Y. Vardi Path Games Erich Grädel (RWTH Aachen, D) Path games are two-player games on nite or innite graphs, where the players, in each move, take a token not just along an edge (as in the common form of graph games), but along a path of any nite length. Path games have been studied in descriptive set theory, in the form of Banach- Mazur games. An important issue in this context is determinacy (does one of the players have a winning strategy?) and its dependency on the topological properties of the winning condition. In a quite dierent setting, path games have been used for task planning in nondeterministic domains. Rather than determinacy (which is obvious for winning conditions in such applications), the main concern there are algorithmic questions. It turns out that planning problems modeled by path games can be solved by automata- based methods. Here we survey path games in a general, abstract setting, but with empha- sis on denability and complexity issues. After a brief review on Banach-Mazur games, we discuss path games that are positionally determined, i.e., admit win- ning strategies that only depend on the current position, not on the history of the play. This can be used to determine the complexity of deciding the winner of path games with LTL winning conditions. Finally we discuss denability issues. We are interested in the question how the logical complexity of dening the win- ning condition (a property of innite paths) is related to the logical complexity of dening who wins the associated game (a property of game graphs). In particular, it turns outthat the winner of path games with LTL winning conditions is denable in CTL*. Keywords: Planning in nondeterministic domains, Banach-Mazur games, logical denability Joint work of: Grädel, Erich; Berwanger, Dietmar; Kreutzer, Stephan Discrete Distributed Games And Tree Automata David Janin (LaBRI Bordeaux, F) Distributed games is a recent multiplayer extension of discrete two player in- nite games. The main motivation for their introduction is that they provide an abstract framework for distributed synthesis problems, in which most known decidable cases can be encoded and solved uniformly. In this talk, we show that this unifying approach allows as well a better understanding of the role played by classical results from tree automata theory (as opposed to adhoc automata constructions) in distributed synthesis problems. Synthesis and Planning 5 More precisely, we use alternating tree automata composition, and simulation of an alternating automaton by a non-deterministic one, as two central tools for giving a simple proof of known decidable cases. Keywords: Distributed games, tree automata, synthesis Decentralized Supervisory Control of Discrete-Event Systems Stéphane Lafortune (University of Michigan, USA) Decentralized control architectures where a set of local controllers jointly con- trol a given distributed system by fusion of their respective control actions are considered. These control architectures arise for instance in the study of networked sys- tems. The framework adopted is that of discrete-event systems, i.e., systems with discrete state spaces and event-driven dynamics. The controllers (or supervisors) observe and control subsets of the events executed by the system. Attention will be focused on the necessary and sucient "coobservability" requirements in order for a set of supervisors to achieve a given desired controlled behavior. Dierent complementary versions of "coobservability" will be discussed, as the amount of inferencing done by the supervisors and the method of fusion of their respective control actions are
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