190,700 research outputs found

    Agent-based agreement over concept meaning using contrast sets

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    We develop a model for 2 agents to reach agreement over concept meaning in specific contexts. The model is based on an argumentation-based communication that engage the agents in a process of mutual adaptation using argumentation to reach an agreement over concept meaning. Our approach is to model concept meaning using the semiotic triangle and the notion of contrast sets. We implement and evaluate present three common sense scenarios where two agents argue and reach agreements over the contextual meaning of concepts. © 2015 The authors and IOS Press. All rights reservedThis paper has been partially supported by projects ESSENCE: Evolution of Shared Semantics in Computational Environments (TIN 607062) and NASAID (CSIC Intramural 201550E022)Peer Reviewe

    Harnessing Higher-Order (Meta-)Logic to Represent and Reason with Complex Ethical Theories

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    The computer-mechanization of an ambitious explicit ethical theory, Gewirth's Principle of Generic Consistency, is used to showcase an approach for representing and reasoning with ethical theories exhibiting complex logical features like alethic and deontic modalities, indexicals, higher-order quantification, among others. Harnessing the high expressive power of Church's type theory as a meta-logic to semantically embed a combination of quantified non-classical logics, our work pushes existing boundaries in knowledge representation and reasoning. We demonstrate that intuitive encodings of complex ethical theories and their automation on the computer are no longer antipodes.Comment: 14 page

    A reconstruction of Classical Utilitarianism

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    The myth of 'the myth of Irish neutrality': deconstructing concepts of Irish neutrality using international relations theories

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    A number of academics, journalists and political elites claim that Irish neutrality is a 'myth', and many also characterise public support for Irish neutrality as 'confused' and 'nonrational'. This 'unneutral' discourse in the academic literature and mainstream Irish media is based on an academic thesis, that of an Unneutral Ireland. The Unneutral thesis constructs a particular concept of neutrality in order to draw its conclusion that Ireland is 'unneutral'. Using a poststructuralist approach--a rarity in the discipline of International Relations (IR)--this paper deconstructs concepts of Irish neutrality using a framework of IR theories. The results show that the concept of neutrality put forward in the Unneutral Ireland thesis and the dominant discourses on Irish neutrality are based on a hegemonic IR theory, the theory of neorealism, rather than on seemingly 'objective' scientific research methods. The paper concludes that non-realist theories and approaches may provide a better understanding of Irish neutrality and of the dynamics of public support for Irish neutrality

    Training an adaptive dialogue policy for interactive learning of visually grounded word meanings

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    We present a multi-modal dialogue system for interactive learning of perceptually grounded word meanings from a human tutor. The system integrates an incremental, semantic parsing/generation framework - Dynamic Syntax and Type Theory with Records (DS-TTR) - with a set of visual classifiers that are learned throughout the interaction and which ground the meaning representations that it produces. We use this system in interaction with a simulated human tutor to study the effects of different dialogue policies and capabilities on the accuracy of learned meanings, learning rates, and efforts/costs to the tutor. We show that the overall performance of the learning agent is affected by (1) who takes initiative in the dialogues; (2) the ability to express/use their confidence level about visual attributes; and (3) the ability to process elliptical and incrementally constructed dialogue turns. Ultimately, we train an adaptive dialogue policy which optimises the trade-off between classifier accuracy and tutoring costs.Comment: 11 pages, SIGDIAL 2016 Conferenc

    Mechanisms for Automated Negotiation in State Oriented Domains

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    This paper lays part of the groundwork for a domain theory of negotiation, that is, a way of classifying interactions so that it is clear, given a domain, which negotiation mechanisms and strategies are appropriate. We define State Oriented Domains, a general category of interaction. Necessary and sufficient conditions for cooperation are outlined. We use the notion of worth in an altered definition of utility, thus enabling agreements in a wider class of joint-goal reachable situations. An approach is offered for conflict resolution, and it is shown that even in a conflict situation, partial cooperative steps can be taken by interacting agents (that is, agents in fundamental conflict might still agree to cooperate up to a certain point). A Unified Negotiation Protocol (UNP) is developed that can be used in all types of encounters. It is shown that in certain borderline cooperative situations, a partial cooperative agreement (i.e., one that does not achieve all agents' goals) might be preferred by all agents, even though there exists a rational agreement that would achieve all their goals. Finally, we analyze cases where agents have incomplete information on the goals and worth of other agents. First we consider the case where agents' goals are private information, and we analyze what goal declaration strategies the agents might adopt to increase their utility. Then, we consider the situation where the agents' goals (and therefore stand-alone costs) are common knowledge, but the worth they attach to their goals is private information. We introduce two mechanisms, one 'strict', the other 'tolerant', and analyze their affects on the stability and efficiency of negotiation outcomes.Comment: See http://www.jair.org/ for any accompanying file

    Own up! Does anyone out there have a decent theory of ownership?

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    In this short paper, I attempt to find what theoretical grounds might support the term ownership as used in aid relations and critically to discuss these grounds. Three possible sources for thinking through the concept are: property rights, relationships made or sustained through gifts, and principal-agent theory. After setting the concept of ownership in development aid within the context of its origins, the paper explores the relevance and implications of seeing ownership as the effect of a gift, and then, in more detail, explores the way in which principal-agent theory has been applied to the analysis of ownership. Where this has been done, a particular controversy emerges around the relationship between ownership and conditionality: some regard these notions as fully compatible while others highlight the tension between them

    Complexity over Uncertainty in Generalized Representational\ud Information Theory (GRIT): A Structure-Sensitive General\ud Theory of Information

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    What is information? Although researchers have used the construct of information liberally to refer to pertinent forms of domain-specific knowledge, relatively few have attempted to generalize and standardize the construct. Shannon and Weaver(1949)offered the best known attempt at a quantitative generalization in terms of the number of discriminable symbols required to communicate the state of an uncertain event. This idea, although useful, does not capture the role that structural context and complexity play in the process of understanding an event as being informative. In what follows, we discuss the limitations and futility of any generalization (and particularly, Shannon’s) that is not based on the way that agents extract patterns from their environment. More specifically, we shall argue that agent concept acquisition, and not the communication of\ud states of uncertainty, lie at the heart of generalized information, and that the best way of characterizing information is via the relative gain or loss in concept complexity that is experienced when a set of known entities (regardless of their nature or domain of origin) changes. We show that Representational Information Theory perfectly captures this crucial aspect of information and conclude with the first generalization of Representational Information Theory (RIT) to continuous domains

    VerbAtlas: a novel large-scale verbal semantic resource and its application to semantic role labeling

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    We present VerbAtlas, a new, hand-crafted lexical-semantic resource whose goal is to bring together all verbal synsets from WordNet into semantically-coherent frames. The frames define a common, prototypical argument structure while at the same time providing new concept-specific information. In contrast to PropBank, which defines enumerative semantic roles, VerbAtlas comes with an explicit, cross-frame set of semantic roles linked to selectional preferences expressed in terms of WordNet synsets, and is the first resource enriched with semantic information about implicit, shadow, and default arguments. We demonstrate the effectiveness of VerbAtlas in the task of dependency-based Semantic Role Labeling and show how its integration into a high-performance system leads to improvements on both the in-domain and out-of-domain test sets of CoNLL-2009. VerbAtlas is available at http://verbatlas.org

    Topic Independent Identification of Agreement and Disagreement in Social Media Dialogue

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    Research on the structure of dialogue has been hampered for years because large dialogue corpora have not been available. This has impacted the dialogue research community's ability to develop better theories, as well as good off the shelf tools for dialogue processing. Happily, an increasing amount of information and opinion exchange occur in natural dialogue in online forums, where people share their opinions about a vast range of topics. In particular we are interested in rejection in dialogue, also called disagreement and denial, where the size of available dialogue corpora, for the first time, offers an opportunity to empirically test theoretical accounts of the expression and inference of rejection in dialogue. In this paper, we test whether topic-independent features motivated by theoretical predictions can be used to recognize rejection in online forums in a topic independent way. Our results show that our theoretically motivated features achieve 66% accuracy, an improvement over a unigram baseline of an absolute 6%.Comment: @inproceedings{Misra2013TopicII, title={Topic Independent Identification of Agreement and Disagreement in Social Media Dialogue}, author={Amita Misra and Marilyn A. Walker}, booktitle={SIGDIAL Conference}, year={2013}
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