210 research outputs found

    Using BATNAs and WATNAs in online dispute resolution

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    When contracting through software agents, disputes will inevitably arise. Thus there is an urgent need to find alternatives to litigation for resolving conflicts. Methods of Online Dispute Resolution (ODR) need to be considered to resolve such disputes. Having agents understanding what the dispute is about, managing all interaction between the parties and even formulating proposed solutions is an important innovation. Hence it is of the utmost relevance that the agents may be able to recognise and evaluate the facts, the position of the parties and understand all the relevant data. In many circumstances, risk management and avoidance will be a crucial point to be considered. In this sense we analyze the usefulness of a parallel concept to BATNA – Best Alternative to Negotiated Agreement, that of a WATNA – Worst Alternative to Negotiated Agreement, allowing the software agents to consider the space between BATNA and WATNA as a useful element to be taken into account when making or accepting a proposal. These software agents embodied with intelligent techniques are integrated in an architecture designed to provide support to the ODR in a system we have developed for the resolution of labour disputes - UMCourt. In this context software agents are used to compute and provide the parties with the best and worst alternative to a negotiated agreement.TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006)Fundação para a Ciência e a Tecnologia (FCT

    A Survey on Legal Question Answering Systems

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    Many legal professionals think that the explosion of information about local, regional, national, and international legislation makes their practice more costly, time-consuming, and even error-prone. The two main reasons for this are that most legislation is usually unstructured, and the tremendous amount and pace with which laws are released causes information overload in their daily tasks. In the case of the legal domain, the research community agrees that a system allowing to generate automatic responses to legal questions could substantially impact many practical implications in daily activities. The degree of usefulness is such that even a semi-automatic solution could significantly help to reduce the workload to be faced. This is mainly because a Question Answering system could be able to automatically process a massive amount of legal resources to answer a question or doubt in seconds, which means that it could save resources in the form of effort, money, and time to many professionals in the legal sector. In this work, we quantitatively and qualitatively survey the solutions that currently exist to meet this challenge.Comment: 57 pages, 1 figure, 10 table

    Large-Scale Legal Reasoning with Rules and Databases

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    Traditionally, computational knowledge representation and reasoning focused its attention on rich domains such as the law. The main underlying assumption of traditional legal knowledge representation and reasoning is that knowledge and data are both available in main memory. However, in the era of big data, where large amounts of data are generated daily, an increasing rangeof scientific disciplines, as well as business and human activities, are becoming data-driven. This chapter summarises existing research on legal representation and reasoning in order to uncover technical challenges associated both with the integration of rules and databases and with the main concepts of the big data landscape. We expect these challenges lead naturally to future research directions towards achieving large scale legal reasoning with rules and databases

    The Effectiveness of the Three-Module Job Training Intervention on Job Search Knowledge, Job Search Attitude Knowledge, and Job Survival/Maintenance Knowledge

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    The purpose of this study was to determine the effectiveness of the Three-Module Job Training Intervention on increasing job search knowledge, job search attitude knowledge, and job survival/maintenance knowledge. The Three-Module Job Training Intervention consists of Module I-Job Search Training (JST); Module II-Job Search Attitude Training (JSAT); and Module III-Job Survival and Maintenance Training (JSMT). In this study, the researcher used three instruments to measure pre-training and post-training levels of job search knowledge, job search attitude knowledge, and job survival/maintenance knowledge. The Job Search Knowledge Scale (JSKS) measured the level of job search knowledge; the Job Search Attitude Inventory (JSAI) measured the level of job search attitude knowledge; and the Job Survival Success Scale (JSSS) measured the level of job survival knowledge. All three instruments were created by John J. Liptak (2009, 2015). According to Liptak (2015), an increase in the participant’s post-training assessment score compared to the participant’s pre-training assessment score indicates an increase in the participant’s level of knowledge. In addition to Liptak’s assessments, the researcher used the Kirkpatrick Four-Level Training Evaluation Model to evaluate the effectiveness of training (D.L., Kirkpatrick & J. D., Kirkpatrick, 2006, 2007). According to the Kirkpatrick and Kirkpatrick (2006, 2007) levels one, two, three, or all four levels may be used to evaluate effectiveness of training. In this study, the researcher evaluated the effectiveness of training at Level I (Reaction) and Level II (Learning). For the evaluation of the Three-Model Job Training Intervention at Level I (Reaction), survey results indicated effectiveness of the Three-Model Job Training Intervention. At Level II (Learning) of the Kirkpatrick Four-Level Training Evaluation Model, Liptak’s assessment tools (JSKS, JSAI, JSSS) were used to measure participants’ pre-training and post-training levels of knowledge. Paired t-tests results indicated that the participants who received training from the Three-Module Job Training Intervention to increase job search knowledge, job search attitude knowledge, and job survival/ maintenance knowledge showed an increase in their levels of knowledge. With an increase in the participants’ level of knowledge in the specified areas, in addition to survey results, this study demonstrated the effectiveness of the Three-Module Job Training Intervention

    Semantic Types, Lexical Sorts and Classifiers

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    We propose a cognitively and linguistically motivated set of sorts for lexical semantics in a compositional setting: the classifiers in languages that do have such pronouns. These sorts are needed to include lexical considerations in a semantical analyser such as Boxer or Grail. Indeed, all proposed lexical extensions of usual Montague semantics to model restriction of selection, felicitous and infelicitous copredication require a rich and refined type system whose base types are the lexical sorts, the basis of the many-sorted logic in which semantical representations of sentences are stated. However, none of those approaches define precisely the actual base types or sorts to be used in the lexicon. In this article, we shall discuss some of the options commonly adopted by researchers in formal lexical semantics, and defend the view that classifiers in the languages which have such pronouns are an appealing solution, both linguistically and cognitively motivated

    Abstract Argumentation / Persuasion / Dynamics

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    The act of persuasion, a key component in rhetoric argumentation, may be viewed as a dynamics modifier. We extend Dung's frameworks with acts of persuasion among agents, and consider interactions among attack, persuasion and defence that have been largely unheeded so far. We characterise basic notions of admissibilities in this framework, and show a way of enriching them through, effectively, CTL (computation tree logic) encoding, which also permits importation of the theoretical results known to the logic into our argumentation frameworks. Our aim is to complement the growing interest in coordination of static and dynamic argumentation.Comment: Arisaka R., Satoh K. (2018) Abstract Argumentation / Persuasion / Dynamics. In: Miller T., Oren N., Sakurai Y., Noda I., Savarimuthu B., Cao Son T. (eds) PRIMA 2018: Principles and Practice of Multi-Agent Systems. PRIMA 2018. Lecture Notes in Computer Science, vol 11224. Springer, Cha

    業績目録(吉本啓)

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    Towards domain-independent conflict resolution tools

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    Given the current state of the legal systems, Online Dispute Resolution tools are being regarded as an alternative way to solve conflicts out of courts, namely under virtual environments. However, the use of these tools is still relatively restricted as they are still few in number and very domain-cantered. Indeed, abstract and conceptual tools whose building blocks could be adapted for particular use would foster the development of ODR systems. In this paper we present this novel line of attack, in which an agent-based architecture is used with the support of an ontology to build an abstract and formal ODR system, independent of the legal domains, but specific enough to be applied to concrete ones. Functionality reuse is maximized, making architectures simpler to implement and to expand.The work described in this paper was developed under the TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), a research project supported by FCT (Science & Technology Foundation), Portugal
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