841 research outputs found

    Current and Future Challenges in Knowledge Representation and Reasoning

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    Knowledge Representation and Reasoning is a central, longstanding, and active area of Artificial Intelligence. Over the years it has evolved significantly; more recently it has been challenged and complemented by research in areas such as machine learning and reasoning under uncertainty. In July 2022 a Dagstuhl Perspectives workshop was held on Knowledge Representation and Reasoning. The goal of the workshop was to describe the state of the art in the field, including its relation with other areas, its shortcomings and strengths, together with recommendations for future progress. We developed this manifesto based on the presentations, panels, working groups, and discussions that took place at the Dagstuhl Workshop. It is a declaration of our views on Knowledge Representation: its origins, goals, milestones, and current foci; its relation to other disciplines, especially to Artificial Intelligence; and on its challenges, along with key priorities for the next decade

    Soundscape in Urban Forests

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    This Special Issue of Forests explores the role of soundscapes in urban forested areas. It is comprised of 11 papers involving soundscape studies conducted in urban forests from Asia and Africa. This collection contains six research fields: (1) the ecological patterns and processes of forest soundscapes; (2) the boundary effects and perceptual topology; (3) natural soundscapes and human health; (4) the experience of multi-sensory interactions; (5) environmental behavior and cognitive disposition; and (6) soundscape resource management in forests

    A Phenomenological Study on Cultivating Empowering Attributes that Promote Successful Living in Graduates of a Social Emotional Learning Program

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    The purpose of this transcendental phenomenological study is to reveal the empowering attributes that promote successful living academically, behaviorally, and socially at home, in school, and in the community as described through the lived experiences of individuals who have completed a social-emotional learning program. The central research question, “What experiences in social-emotional learning impact the behaviors of individuals who have completed SEL programs?”, is developed to gather the lived experiences that describe how SEL influences the conduct of various people. This study is guided by Bandura’s social learning theory, which focuses on the significance of observing, emulating, and modeling attitudes and actions of others to impact human behavior. This concept relates to social-emotional learning through the SEL programs’ emphasis on promoting diversity, increasing skill in managing emotions, goal setting, and making responsible decisions. Various perceptions of the participants’ experiences will be collected in interviews, focus groups, and a document analysis. These descriptions will be assembled through a thematic analysis to determine the patterns and similarities of the individuals’ views and attitudes regarding their participation in social-emotional learning programs

    An investigation into collaborative practice between the class teacher, special education teacher (SET) and speech and language therapist to identify and meet the needs of students with speech, language and communication difficulties (SLCD) in Irish primary schools

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    The number of students presenting with Speech, Language and Communication Difficulties (SLCD) represents a significant cohort of the student population nationally and internationally, according to the literature. These students require specialised in-school support from school staff as well as support from external professionals such as Speech and Language Therapists (SLTs). This research set out to investigate the nature and extent of collaborative practice in Irish primary schools to identify and meet the needs of students with SLCD. A social constructivist paradigm was adopted for the investigation to ensure that the various perspectives and multiple realities of principals, class teachers, SETs, and SLTs were identified and validated. The study adopted a qualitative approach and the researcher employed semi-structured interviews as her primary data collection method. The research was conducted in four main cluster groups in the greater Dublin area, which enabled the researcher to examine the lived experiences of the participants. The researcher utilised the theoretical framework of Lave and Wenger’s Community of Practice (CoP) (1991), as a lens for analysis. Thematic analysis of the dataset, guided by the theoretical framework, unveiled a number of significant findings. In summary, findings suggest that while the value of collaborative practice is acknowledged as necessary in meeting the needs of students with SLCD, participants reported common issues that challenge effective collaborative practice. The nature of these challenges was identified as being a lack of time to engage, the absence of a shared knowledge and the limitations of current Continued Professional Development (CPD) around curricular change, such as the introduction and implementation of the Primary Language Curriculum, by the Department of Education in 2019. The study suggests that due to these impediments, effective collaborative practice has been hindered and thus, the needs of students with SLCD are not being appropriately identified or addressed. Finally, this study argues that collaborative practice and the development of CoPs are required to effectively meet the needs of students with SLCD in inclusive classrooms, which are increasingly diverse. This study offers some key recommendations which may inform future policy and practice, in relation to multidisciplinary collaboration in schools, approaches to Initial Teacher Education and CPD. Frameworks, emerging from the data, are provided which may usefully guide the establishment of meaningful CoPs, enhanced ITE and approached to CPD, so that stakeholders can effectively identify and meet the needs of all students, particularly those with SLCD in their own context of practice.N

    Northeastern Illinois University, Academic Catalog 2023-2024

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    https://neiudc.neiu.edu/catalogs/1064/thumbnail.jp

    Explanations as Programs in Probabilistic Logic Programming

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    The generation of comprehensible explanations is an essential feature of modern artificial intelligence systems. In this work, we consider probabilistic logic programming, an extension of logic programming which can be useful to model domains with relational structure and uncertainty. Essentially, a program specifies a probability distribution over possible worlds (i.e., sets of facts). The notion of explanation is typically associated with that of a world, so that one often looks for the most probable world as well as for the worlds where the query is true. Unfortunately, such explanations exhibit no causal structure. In particular, the chain of inferences required for a specific prediction (represented by a query) is not shown. In this paper, we propose a novel approach where explanations are represented as programs that are generated from a given query by a number of unfolding-like transformations. Here, the chain of inferences that proves a given query is made explicit. Furthermore, the generated explanations are minimal (i.e., contain no irrelevant information) and can be parameterized w.r.t. a specification of visible predicates, so that the user may hide uninteresting details from explanations.Comment: Published as: Vidal, G. (2022). Explanations as Programs in Probabilistic Logic Programming. In: Hanus, M., Igarashi, A. (eds) Functional and Logic Programming. FLOPS 2022. Lecture Notes in Computer Science, vol 13215. Springer, Cham. The final authenticated publication is available online at https://doi.org/10.1007/978-3-030-99461-7_1

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    On the Introduction of Guarded Lists in Bach: Expressiveness, Correctness, and Efficiency Issues

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    Concurrency theory has received considerable attention, but mostly in the scope of synchronous process algebras such as CCS, CSP, and ACP. As another way of handling concurrency, data-based coordination languages aim to provide a clear separation between interaction and computation by synchronizing processes asynchronously by means of information being available or not on a shared space. Although these languages enjoy interesting properties, verifying program correctness remains challenging. Some works, such as Anemone, have introduced facilities, including animations and model checking of temporal logic formulae, to better grasp system modelling. However, model checking is known to raise performance issues due to the state space explosion problem. In this paper, we propose a guarded list construct as a solution to address this problem. We establish that the guarded list construct increases performance while strictly enriching the expressiveness of data-based coordination languages. Furthermore, we introduce a notion of refinement to introduce the guarded list construct in a correctness-preserving manner.Comment: In Proceedings ICE 2023, arXiv:2308.0892
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