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Documents authored by Dimitrova, Rayna

Document
DOI: 10.4230/LIPIcs.CONCUR.2017.13
The Robot Routing Problem for Collecting Aggregate Stochastic Rewards

Authors: Rayna Dimitrova, Ivan Gavran, Rupak Majumdar, Vinayak S. Prabhu, and Sadegh Esmaeil Zadeh Soudjani

Published in: LIPIcs, Volume 85, 28th International Conference on Concurrency Theory (CONCUR 2017)

Abstract
We propose a new model for formalizing reward collection problems on graphs with dynamically generated rewards which may appear and disappear based on a stochastic model. The robot routing problem is modeled as a graph whose nodes are stochastic processes generating potential rewards over discrete time. The rewards are generated according to the stochastic process, but at each step, an existing reward disappears with a given probability. The edges in the graph encode the (unit-distance) paths between the rewards' locations. On visiting a node, the robot collects the accumulated reward at the node at that time, but traveling between the nodes takes time. The optimization question asks to compute an optimal (or epsilon-optimal) path that maximizes the expected collected rewards. We consider the finite and infinite-horizon robot routing problems. For finite-horizon, the goal is to maximize the total expected reward, while for infinite horizon we consider limit-average objectives. We study the computational and strategy complexity of these problems, establish NP-lower bounds and show that optimal strategies require memory in general. We also provide an algorithm for computing epsilon-optimal infinite paths for arbitrary epsilon > 0.
Cite as

Rayna Dimitrova, Ivan Gavran, Rupak Majumdar, Vinayak S. Prabhu, and Sadegh Esmaeil Zadeh Soudjani. The Robot Routing Problem for Collecting Aggregate Stochastic Rewards. In 28th International Conference on Concurrency Theory (CONCUR 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 85, pp. 13:1-13:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{dimitrova_et_al:LIPIcs.CONCUR.2017.13,
  author =	{Dimitrova, Rayna and Gavran, Ivan and Majumdar, Rupak and Prabhu, Vinayak S. and Soudjani, Sadegh Esmaeil Zadeh},
  title =	{{The Robot Routing Problem for Collecting Aggregate Stochastic Rewards}},
  booktitle =	{28th International Conference on Concurrency Theory (CONCUR 2017)},
  pages =	{13:1--13:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-048-4},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{85},
  editor =	{Meyer, Roland and Nestmann, Uwe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2017.13},
  URN =		{urn:nbn:de:0030-drops-77920},
  doi =		{10.4230/LIPIcs.CONCUR.2017.13},
  annote =	{Keywords: Path Planning, Graph Games, Quantitative Objectives, Discounting}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2008.1751
Abstraction Refinement for Games with Incomplete Information

Authors: Rayna Dimitrova and Bernd Finkbeiner

Published in: LIPIcs, Volume 2, IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (2008)

Abstract
Counterexample-guided abstraction refinement (CEGAR) is used in automated software analysis to find suitable finite-state abstractions of infinite-state systems. In this paper, we extend CEGAR to games with incomplete information, as they commonly occur in controller synthesis and modular verification. The challenge is that, under incomplete information, one must carefully account for the knowledge available to the player: the strategy must not depend on information the player cannot see. We propose an abstraction mechanism for games under incomplete information that incorporates the approximation of the players\' moves into a knowledge-based subset construction on the abstract state space. This abstraction results in a perfect-information game over a finite graph. The concretizability of abstract strategies can be encoded as the satisfiability of strategy-tree formulas. Based on this encoding, we present an interpolation-based approach for selecting new predicates and provide sufficient conditions for the termination of the resulting refinement loop.
Cite as

Rayna Dimitrova and Bernd Finkbeiner. Abstraction Refinement for Games with Incomplete Information. In IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science. Leibniz International Proceedings in Informatics (LIPIcs), Volume 2, pp. 175-186, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{dimitrova_et_al:LIPIcs.FSTTCS.2008.1751,
  author =	{Dimitrova, Rayna and Finkbeiner, Bernd},
  title =	{{Abstraction Refinement for Games with Incomplete Information}},
  booktitle =	{IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science},
  pages =	{175--186},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-08-8},
  ISSN =	{1868-8969},
  year =	{2008},
  volume =	{2},
  editor =	{Hariharan, Ramesh and Mukund, Madhavan and Vinay, V},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2008.1751},
  URN =		{urn:nbn:de:0030-drops-17510},
  doi =		{10.4230/LIPIcs.FSTTCS.2008.1751},
  annote =	{Keywords: Automatic abstraction refinement, synthesis}
}
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