467 research outputs found
Is a Semantic Web Agent a Knowledge-Savvy Agent?
No full textThe issue of knowledge sharing has permeated the field of distributed AI and in particular, its successor, multiagent systems. Through the years, many research and engineering efforts have tackled the problem of encoding and sharing knowledge without the need for a single, centralized knowledge base. However, the emergence of modern computing paradigms such as distributed, open systems have highlighted the importance of sharing distributed and heterogeneous knowledge at a larger scale—possibly at the scale of the Internet. The very characteristics that define the Semantic Web—that is, dynamic, distributed, incomplete, and uncertain knowledge—suggest the need for autonomy in distributed software systems. Semantic Web research promises more than mere management of ontologies and data through the definition of machine-understandable languages. The openness and decentralization introduced by multiagent systems and service-oriented architectures give rise to new knowledge management models, for which we can’t make a priori assumptions about the type of interaction an agent or a service may be engaged in, and likewise about the message protocols and vocabulary used. We therefore discuss the problem of knowledge management for open multi-agent systems, and highlight a number of challenges relating to the exchange and evolution of knowledge in open environments, which pertinent to both the Semantic Web and Multi Agent System communities alike
Using Ontology Modularization for Efficient Negotiation over Ontology Correspondences in MAS
No full textEfficient agent communication in open and dynamic environments relies on the agents ability to reach a mutual understanding over message exchanges. Such environments are characterized by the existence of heterogeneous agents that commit to different ontologies, with no prior assumptions regarding the use of shared vocabularies. Various approaches have therefore considered how mutually acceptable mappings may be determined dynamically between agents through negotiation. In particular, this paper focusses on the meaning based negotiation approach, proposed by Laera et al [1], that makes use of argumentation in order to select a set of mappings that is deemed acceptable by both agents. However, this process can be highly complex, reaching ?(p)2 complete. Whilst it is non-trivial to reduce this complexity, we have explored the use of ontology modularization as a means of reducing the space of possible concepts over which the agents have to negotiate. In this paper, we propose an approach that combines modularization with argumentation to generate focused domains of discourse to facilitate communication. We empirically demonstrate that we can not only reduce the number of alignments required to reach consensus by an average of 75%, but that in 41% of cases, we can identify those agents that would not be able to fully satisfy the request, without the need for negotiation
Data and code release for Carleton, Cornetet, Huybers, Meng & Proctor (preprint, 2020), "Ultraviolet radiation decreases COVID-19 growth rates: Global causal estimates and seasonal implications"
No full textThis upload contains all replication material for "Ultraviolet radiation decreases COVID-19 growth rates: Global causal estimates and seasonal implications" (preprint). Please note that this manuscript is under review and the data and code are likely to change (updated versions will be uploaded to Zenodo as soon as they are available).
Authors: Tamma Carleton, Jules Cornetet, Peter Huybers, Kyle C. Meng, Jonathan Proctor.
Code is located within CCHMP_covid_climate_code_release.zip, and is written in R, Stata, and Matlab. The working directory should be set to the repository folder at the top of each script.
Please find the code needed to replicate the main findings of the paper described below:
Plots of data: R and Stata scripts to make figures 1B, S1, S2, S3, S4 and S13 can be found within “code/analysis/data_plots/”.
Regression analysis: Stata scripts to run the distributed lag regressions and plot the results in figures 2, S6, S7, S8 and S9 can be found within “code/analysis/regressions/”
Seasonal simulations: R and Stata scripts to replicate the seasonal simulation shown in figures 3, S5 and S10 can be found within “code/analysis/seasonal_sim/”.
SEIR simulations: Matlab scripts to replicate the SEIR simulations shown in figures S11 and S12 can be found within “code/analysis/SEIR/”.
Data are located within CCHMP_covid_climate_data_release.zip
Dynamic selection of ontological alignments: a space reduction mechanism
No full textEffective communication in open environments relies on the ability of agents to reach a mutual understanding of the exchanged message by reconciling the vocabulary (ontology) used. Various approaches have considered how mutually acceptable mappings between corresponding concepts in the agents' own ontologies may be determined dynamically through argumentation-based negotiation (such as Meaning-based Argumentation). However, the complexity of this process is high, approaching Π2(p)-complete in some cases. As reducing this complexity is non-trivial, we propose the use of ontology modularization as a means of reducing the space over which possible concepts are negotiated. The suitability of different modularization approaches as filtering mechanisms for reducing the negotiation search space is investigated, and a framework that integrates modularization with Meaning-based Argumentation is proposed. We empirically demonstrate that some modularization approaches not only reduce the number of alignments required to reach consensus, but also predict those cases where a service provider is unable to fully satisfy a request, without the need for negotiation
Data and code release for Carleton, Cornetet, Huybers, Meng & Proctor (PNAS, 2020), "Global evidence for ultraviolet radiation decreasing COVID-19 growth rates"
No full text<p>This upload contains all replication material for "Global evidence for ultraviolet radiation decreasing COVID-19 growth rates" (PNAS, 2020). Please note that previous versions of this upload provided data and code for the pre-print version of the article, which changed somewhat through the peer review process. </p>
<p><strong>Authors:</strong> Tamma Carleton, Jules Cornetet, Peter Huybers, Kyle C. Meng, Jonathan Proctor.</p>
<p><strong>Code is located within CCHMP_covid_climate_code_release.zip</strong>, and is written in R, Stata, and Matlab. The working directory should be set to the repository folder at the top of each script (all other filepaths are relative).</p>
<p>Please find the code needed to replicate the main findings of the paper described below:</p>
<ul>
<li>Plots of data: R and Stata scripts to make figures 1B, 2A/B/C, S1, S2, and S3, can be found within “code/analysis/data_plots/”.</li>
<li>Regression analysis: Stata scripts to run the distributed lag regressions and plot the results in figures 2, 3C, S5, S6, S7, S8, S10, and S14, as well as Table S1, can be found within “code/analysis/regressions/”. R scripts for data analysis and plotting for figures 3A/B and S9 are also within "code/analysis/regressions/".</li>
<li>Seasonal simulations: R and Stata scripts to replicate the seasonal simulation shown in figures 4, S4 and S11 can be found within “code/analysis/seasonal_sim/”.</li>
<li>SEIR simulations: Matlab scripts to replicate the SEIR simulations shown in figures S12 and S13 can be found within “code/analysis/SEIR/”.</li>
</ul>
<p><strong>Data are located within CCHMP_covid_climate_data_release.zip.</strong></p>
Deciding agent orientation on ontology mappings
No full textEffective communication in open environments relies on the ability of agents to reach a mutual understanding of the exchanged message by reconciling the vocabulary (ontology) used. Various approaches have considered how mutually acceptable mappings between corresponding concepts in the agents’ own ontologies may be determined dynamically through argumentation-based negotiation (such as Meaning-based Argumentation, MbA). In this paper we present a novel approach to the dynamic determination of mutually acceptable mappings, that allows agents to express a private acceptability threshold over the types of mappings they prefer. We empirically compare this approach with the Meaning-based Argumentation and demonstrate that the proposed approach produces larger agreed alignments thus better enabling agent communication. Furthermore, we compare and evaluate the fitness for purpose of the generated alignments, and we empirically demonstrate that the proposed approach has comparable performance to the MbA approach
Competizione e competitività nel settore alberghiero italiano. Alcuni aspetti di un problema complesso
No full textAutocrine/Paracrine Loop Between SCF+/c-Kit+ Mast Cells Promotes Cutaneous Melanoma Progression
No full textc-Kit, or mast/stem cell growth factor receptor Kit, is a tyrosine kinase receptor structurally analogous to the colony-stimulating factor-1 (CSF-1) and platelet-derived growth factor (PDGF) CSF-1/PDGF receptor Tyr-subfamily. It binds the cytokine KITLG/SCF to regulate cell survival and proliferation, hematopoiesis, stem cell maintenance, gametogenesis, mast cell development, migration and function, and it plays an essential role in melanogenesis. SCF and c-Kit are biologically active as membrane-bound and soluble forms. They can be expressed by tumor cells and cells of the microenvironment playing a crucial role in tumor development, progression, and relapses. To date, few investigations have concerned the role of SCF+/c-Kit+ mast cells in normal, premalignant, and malignant skin lesions that resemble steps of malignant melanoma progression. In this study, by immunolabeling reactions, we demonstrated that in melanoma lesions, SCF and c-Kit were expressed in mast cells and released by themselves, suggesting an autocrine/paracrine loop might be implicated in regulatory mechanisms of neoangiogenesis and tumor progression in human melanoma
Evaluating Ontology Modules Using an Entropy Inspired Metric
No full textThe focus of ontology modularization to date has largely been on the creation of techniques to carry out ontology modularization. This creates a problem in evaluating the results of the different techniques. Ontology modularization techniques cannot solely be evaluated by examining their logical properties. Certain applications of ontology modularization, such as ontology reuse, require a new objective way to evaluate the results. This paper motivates the use of an entropy inspired measure to evaluate ontology modules by arguing that current objective measures of evaluation do not reconcile with the subjective measures employed by Ontology Engineers. Experiments are conducted to show that an entropy based evaluation of ontology modules is beneficial to an Ontology Engineer evaluating the results of ontology module extraction techniques
- …
