liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Drakengren, Thomas
    et al.
    Linköping University, The Institute of Technology.
    Bjäreland, Marcus
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Reasoning about action in polynomial time1999In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 115, no 1, p. 1-24Article in journal (Refereed)
    Abstract [en]

    Although many formalisms for reasoning about action exist, surprisingly few approaches have taken computational complexity into consideration. The contributions of this article are the following: a temporal logic with a restriction for which deciding satisfiability is tractable, a tractable extension for reasoning about action, and NP-completeness results for the unrestricted problems. Many interesting reasoning problems can be modelled, involving nondeterminism, concurrency and memory of actions. The reasoning process is proved to be sound and complete. (C) 1999 Published by Elsevier Science B.V. All rights reserved.

  • 2.
    Gustafsson, Joakim
    et al.
    Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab. Linköping University, The Institute of Technology.
    Kvarnström, Jonas
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Elaboration tolerance through object-orientation2004In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 153, no 1-2, p. 239-285Article in journal (Refereed)
    Abstract [en]

    Although many formalisms for reasoning about action and change have been proposed in the literature, any concrete examples provided in such articles have primarily consisted of tiny domains that highlight some particular aspect or problem. However, since some of the classical problems are now completely or partially solved and since powerful tools are becoming available, it is now necessary to start modeling more complex domains. This article presents a methodology for handling such domains in a systematic manner using an object-oriented framework and provides several examples of the elaboration tolerance exhibited by the resulting models. (C) 2003 Elsevier B.V. All rights reserved.

  • 3.
    Jonsson, Anders
    et al.
    University of Pompeu Fabra, Spain .
    Jonsson, Peter
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Lööw, Tomas
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Limitations of acyclic causal graphs for planning2014In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 210, p. 36-55Article in journal (Refereed)
    Abstract [en]

    Causal graphs are widely used in planning to capture the internal structure of planning instances. Researchers have paid special attention to the subclass of planning instances with acyclic causal graphs, which in the past have been exploited to generate hierarchical plans, to compute heuristics, and to identify classes of planning instances that are easy to solve. This naturally raises the question of whether planning is easier when the causal graph is acyclic. In this article we show that the answer to this question is no, proving that in the worst case, the problem of plan existence is PSPACE-complete even when the causal graph is acyclic. Since the variables of the planning instances in our reduction are propositional, this result applies to STRIPS planning with negative preconditions. We show that the reduction still holds if we restrict actions to have at most two preconditions. Having established that planning is hard for acyclic causal graphs, we study two subclasses of planning instances with acyclic causal graphs. One such subclass is described by propositional variables that are either irreversible or symmetrically reversible. Another subclass is described by variables with strongly connected domain transition graphs. In both cases, plan existence is bounded away from PSPACE, but in the latter case, the problem of bounded plan existence is hard, implying that optimal planning is significantly harder than satisficing planning for this class.

  • 4.
    Jonsson, Peter
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Constants and finite unary relations in qualitative constraint reasoning2018In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 257Article in journal (Refereed)
    Abstract [en]

    Extending qualitative CSPs with the ability of restricting selected variables to finite sets of possible values has been proposed as an interesting research direction with important applications, cf. "Qualitative constraint satisfaction problems: an extended framework with landmarks" by Li, Liu, and Wang (2013) [48]. Previously presented complexity results for this kind of extended formalisms have typically focused on concrete examples and not on general principles. We propose three general methods. The first two methods are based on analysing the given CSP from a model-theoretical perspective, while the third method is based on directly analysing the growth of the representation of solutions. We exemplify the methods on temporal and spatial formalisms including Allens algebra and RCC-5. (C) 2017 Elsevier B.V. All rights reserved.

  • 5.
    Jonsson, Peter
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, TCSLAB - Theoretical Computer Science Laboratory.
    Haslum, Patrik
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab.
    Bäckström, Christer
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, TCSLAB - Theoretical Computer Science Laboratory.
    Towards efficient universal planning: A randomized approach2000In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 117, no 1, p. 1-29Article in journal (Refereed)
    Abstract [en]

    One of the most widespread approaches to reactive planning is Schoppers' universal plans. We propose a stricter definition of universal plans which guarantees a weak notion of soundness, not present in the original definition, and isolate three different types of completeness that capture different behaviors exhibited by universal plans. We show that universal plans which run in polynomial time and are of polynomial size cannot satisfy even the weakest type of completeness unless the polynomial hierarchy collapses. By relaxing either the polynomial time or the polynomial space requirement, the construction of universal plans satisfying the strongest type of completeness becomes trivial. As an alternative approach, we study randomized universal planning. By considering a randomized version of completeness and a restricted (but nontrivial) class of problems, we show that there exists randomized universal plans running in polynomial time and using polynomial space which are sound and complete for the restricted class of problems. We also report experimental results on this approach to planning, showing that the performance of a randomized planner is not easily compared to that of a deterministic planner.

  • 6.
    Jonsson, Peter
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, TCSLAB - Theoretical Computer Science Laboratory.
    Krokhin, A.
    Department of Computer Science, University of Warwick, United Kingdom, Department of Computer Science, University of Durham, Durham DH1 3LE, United Kingdom.
    Complexity classification in qualitative temporal constraint reasoning2004In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 160, no 1-2, p. 35-51Article in journal (Refereed)
    Abstract [en]

    We study the computational complexity of the qualitative algebra which is a temporal constraint formalism that combines the point algebra, the point-interval algebra and Allen's interval algebra. We identify all tractable fragments and show that every other fragment is NP-complete. © 2004 Elsevier B.V. All rights reserved.

  • 7.
    Jonsson, Peter
    et al.
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, Faculty of Science & Engineering.
    Lagerkvist, Victor
    Technical University of Dresden, Germany.
    An initial study of time complexity in infinite-domain constraint satisfaction2017In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 245, p. 115-133Article in journal (Refereed)
    Abstract [en]

    The constraint satisfaction problem (CSP) is a widely studied problem with numerous applications in computer science and artificial intelligence. For infinite-domain CSPs, there are many results separating tractable and NP-hard cases while upper and lower bounds on the time complexity of hard cases are virtually unexplored, Hence, we initiate a study of the worst-case time complexity of such CSPs, We analyze backtracking algorithms and determine upper bounds on their time complexity. We present asymptotically faster algorithms based on enumeration techniques and we show that these algorithms are applicable to well-studied problems in, for instance, temporal reasoning. Finally, we prove non-trivial lower bounds applicable to many interesting CSPs, under the assumption that certain complexity-theoretic assumptions hold. The gap between upper and lower bounds is in many cases surprisingly small, which suggests that our upper bounds cannot be significantly improved. (C) 2017 Elsevier B.V. All rights reserved.

  • 8.
    Jonsson, Peter
    et al.
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Lööw, Tomas
    Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
    Computational complexity of linear constraints over the integers2013In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 195, p. 44-62Article in journal (Refereed)
    Abstract [en]

    Temporal reasoning problems arise in many areas of Al, including planning, natural language understanding, and reasoning about physical systems. The computational complexity of continuous-time temporal constraint reasoning is fairly well understood. There are, however, many different cases where discrete time must be considered; various scheduling problems and reasoning about sampled physical systems are two examples. Here, the complexity of temporal reasoning is not as well-studied nor as well-understood. In order to get a better understanding, we consider the powerful Horn disjunctive linear relations (Horn DLR) formalism adapted for discrete time and study its computational complexity. We show that the full formalism is NP-hard and identify several maximal tractable subclasses. We also lift the maximality results to obtain hardness results for other families of constraints. Finally, we discuss how the results and techniques presented in this paper can be used for studying even more expressive classes of temporal constraints.

  • 9.
    Nordh, Gustav
    et al.
    Ecole Polytechnique.
    Zanuttini, Bruno
    Universite de Caen.
    What makes propositional abduction tractable2008In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 172, no 10, p. 1245-1284Article in journal (Refereed)
  • 10.
    Sandewall, Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, CASL - Cognitive Autonomous Systems Laboratory.
    A Review of the Handbook of Knowledge Representation.2008In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 172, no 18, p. 1965-1966Article, book review (Other academic)
    Abstract [en]

    The newly appeared Handbook of Knowledge Representation is an impressive piece of work. Its three editors and its forty-five contributors have produced twenty-five concise, textbook-style chapters that introduce most of the major aspects of the science of knowledge representation. Reading this book is a very positive experience: it demonstrates the breadth, the depth and the coherence that our field has achieved by now.

  • 11.
    Sandewall, Erik
    Linköping University, Department of Computer and Information Science, CASL - Cognitive Autonomous Systems Laboratory. Linköping University, The Institute of Technology.
    Defeasible inheritance with doubt index and its axiomatic characterization2010In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 174, no 18, p. 1431-1459Article in journal (Refereed)
    Abstract [en]

    This article introduces and uses a representation of defeasible inheritance networks where links in the network are viewed as propositions, and where defeasible links are tagged with a quantitative indication of the proportion of exceptions, called the doubt index. This doubt index is used for restricting the length of the chains of inference. The representation also introduces the use of defeater literals that disable the chaining of subsumption links. The use of defeater literals replaces the use of negative defeasible inheritance links, expressing "most A are not B". The new representation improves the expressivity significantly. Inference in inheritance networks is defined by a combination of axioms that constrain the contents of network extensions, a heuristic restriction that also has that effect, and a nonmonotonic operation of minimizing the set of defeater literals while retaining consistency. We introduce an underlying semantics that defines the meaning of literals in a network, and prove that the axioms are sound with respect to this semantics. We also discuss the conditions for obtaining completeness. Traditional concepts, assumptions and issues in research on nonmonotonic or defeasible inheritance are reviewed in the perspective of this approach.

  • 12.
    Sandewall, Erik
    Linköping University, Department of Computer and Information Science, CASL - Cognitive Autonomous Systems Laboratory. Linköping University, The Institute of Technology.
    From systems to logic in the early development of nonmonotonic reasoning2011In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 175, no 1, p. 416-427Article in journal (Refereed)
    Abstract [en]

    This note describes how the notion of nonmonotonic reasoning emerged in Artificial Intelligence from the mid-1960s to 1980. It gives particular attention to the interplay between three kinds of activities: design of high-level programming systems for AI, design of truth-maintenance systems, and the development of nonmonotonic logics. This was not merely a development from logic to implementation: in several cases there was a development from a system design to a corresponding logic. The article concludes with some reflections on the roles and relationships between logicist theory and system design in AI, and in particular in Knowledge Representation.

  • 13.
    Sandewall, Erik Johan
    Linköping University, The Institute of Technology. Linköping University, Department of Computer and Information Science, CASL - Cognitive Autonomous Systems Laboratory.
    M. Shanahan, Solving the Frame Problem2000In: Artificial Intelligence, ISSN 0004-3702, E-ISSN 1872-7921, Vol. 123, no 1-2, p. 271-273Article, review/survey (Other academic)
1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf