23 found
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Paul E. Dunne [21]Paul Dunne [2]
  1.  10
    Audiences in argumentation frameworks.Trevor J. M. Bench-Capon, Sylvie Doutre & Paul E. Dunne - 2007 - Artificial Intelligence 171 (1):42-71.
  2.  9
    Coherence in finite argument systems.Paul E. Dunne & T. J. M. Bench-Capon - 2002 - Artificial Intelligence 141 (1-2):187-203.
  3.  10
    Weighted argument systems: Basic definitions, algorithms, and complexity results.Paul E. Dunne, Anthony Hunter, Peter McBurney, Simon Parsons & Michael Wooldridge - 2011 - Artificial Intelligence 175 (2):457-486.
  4.  17
    Characteristics of multiple viewpoints in abstract argumentation.Paul E. Dunne, Wolfgang Dvořák, Thomas Linsbichler & Stefan Woltran - 2015 - Artificial Intelligence 228 (C):153-178.
  5.  12
    Strong admissibility revisited: Theory and applications.Martin Caminada & Paul Dunne - forthcoming - Argument and Computation:1-24.
  6.  7
    Computational properties of argument systems satisfying graph-theoretic constraints.Paul E. Dunne - 2007 - Artificial Intelligence 171 (10-15):701-729.
  7.  7
    The computational complexity of ideal semantics.Paul E. Dunne - 2009 - Artificial Intelligence 173 (18):1559-1591.
  8.  8
    Two party immediate response disputes: Properties and efficiency.Paul E. Dunne & T. J. M. Bench-Capon - 2003 - Artificial Intelligence 149 (2):221-250.
  9.  9
    Algorithms for decision problems in argument systems under preferred semantics.Samer Nofal, Katie Atkinson & Paul E. Dunne - 2014 - Artificial Intelligence 207 (C):23-51.
  10.  6
    On the computational complexity of qualitative coalitional games.Michael Wooldridge & Paul E. Dunne - 2004 - Artificial Intelligence 158 (1):27-73.
  11.  7
    On the computational complexity of coalitional resource games.Michael Wooldridge & Paul E. Dunne - 2006 - Artificial Intelligence 170 (10):835-871.
  12.  11
    Automata for infinite argumentation structures.Pietro Baroni, Federico Cerutti, Paul E. Dunne & Massimiliano Giacomin - 2013 - Artificial Intelligence 203 (C):104-150.
  13.  11
    Parametric properties of ideal semantics.Paul E. Dunne, Wolfgang Dvořák & Stefan Woltran - 2013 - Artificial Intelligence 202 (C):1-28.
  14.  11
    Solving coalitional resource games.Paul E. Dunne, Sarit Kraus, Efrat Manisterski & Michael Wooldridge - 2010 - Artificial Intelligence 174 (1):20-50.
  15.  27
    Senses of ‘argument’ in instantiated argumentation frameworks.Adam Wyner, Trevor Bench-Capon, Paul Dunne & Federico Cerutti - 2015 - Argument and Computation 6 (1):50-72.
    Argumentation Frameworks provide a fruitful basis for exploring issues of defeasible reasoning. Their power largely derives from the abstract nature of the arguments within the framework, where arguments are atomic nodes in an undifferentiated relation of attack. This abstraction conceals different senses of argument, namely a single-step reason to a claim, a series of reasoning steps to a single claim, and reasoning steps for and against a claim. Concrete instantiations encounter difficulties and complexities as a result of conflating these senses. (...)
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  16.  3
    The complexity of contract negotiation.Paul E. Dunne, Michael Wooldridge & Michael Laurence - 2005 - Artificial Intelligence 164 (1-2):23-46.
  17.  23
    A logical characterisation of qualitative coalitional games.Paul E. Dunne, Wiebe van der Hoek & Michael Wooldridge - 2007 - Journal of Applied Non-Classical Logics 17 (4):477-509.
    Qualitative coalitional games (QCGs) were introduced as abstract formal models of goal-oriented cooperative systems. A QCG is a game in which each agent is assumed to have some goal to achieve, and in which agents must typically cooperate with others in order to satisfy their goals. In this paper, we show how it is possible to reason about QCGs using Coalition Logic (CL), a formalism intended to facilitate reasoning about coalitional powers in game-like multiagent systems. We introduce a correspondence relation (...)
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  18.  11
    Decidability in argumentation semantics.Paul E. Dunne - forthcoming - Argument and Computation:1-14.
    Much of the formal study of algorithmic concerns with respect to semantics for abstract argumentation frameworks has focused on the issue of computational complexity. In contrast matters regarding computability have been largely neglected. Recent trends in semantics have, however, started to concentrate not so much on the formulation of novel semantics but more on identifying common properties: for example, from basic ideas such as conflict-freeness through to quite sophisticated ideas such as serializability. The aim of this paper is to look (...)
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  19.  15
    Toward feasible and efficient DNA computation.Martyn Amos, Alan Gibbons & Paul E. Dunne - 1998 - Complexity 4 (1):20-24.
  20.  43
    A value-based argument model of convention degradation.Paul E. Dunne - 2005 - Artificial Intelligence and Law 13 (1):153-188.
    The analysis of how social conventions emerge and become established is rightly viewed as a significant study of great relevance to models of legal and social systems. Such conventions, however, do not operate in a monotonic fashion, i.e. the fact that a convention is recognised and complied with at some instant is no guarantee it will continue to be so indefinitely. In total rules and protocols may evolve, with or without the consent of individual members of the society, even to (...)
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  21.  7
    Characterizing strongly admissible sets.Paul E. Dunne - 2020 - Argument and Computation 11 (3):239-255.
    The concept of strong admissibility plays an important role in dialectical proof procedures for grounded semantics allowing, as it does, concise proofs that an argument belongs to the grounded extension without having necessarily to construct this extension in full. One consequence of this property is that strong admissibility ceases to be a unique status semantics. In fact it is straightforward to construct examples for which the number of distinct strongly admissible sets is exponential in the number of arguments. We are (...)
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  22.  13
    The maximum length of prime implicates for instances of 3-SAT.Paul E. Dunne & Trevor J. M. Bench-Capon - 1997 - Artificial Intelligence 92 (1-2):317-329.
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  23.  68
    Argumentation in AI and law: Editors' introduction. [REVIEW]Trevor J. M. Bench-Capon & Paul E. Dunne - 2005 - Artificial Intelligence and Law 13 (1):1-8.