336 research outputs found

    A generic domain pruning technique for GDL-based DCOP algorithms in cooperative multi-agent systems

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    Generalized Distributive Law (GDL) based message passing algorithms, such as Max-Sum and Bounded Max-Sum, are often used to solve distributed constraint optimization problems in cooperative multi-agent systems (MAS). However, scalability becomes a challenge when these algorithms have to deal with constraint functions with high arity or variables with a large domain size. In either case, the ensuing exponential growth of search space can make such algorithms computationally infeasible in practice. To address this issue, we develop a generic domain pruning technique that enables these algorithms to be effectively applied to larger and more complex problems. We theoretically prove that the pruned search space obtained by our approach does not affect the outcome of the algorithms. Moreover, our empirical evaluation illustrates a significant reduction of the search space, ranging from 33% to 81%, without affecting the solution quality of the algorithms, compared to the state-of-the-art

    AED: An Anytime Evolutionary DCOP Algorithm

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    Evolutionary optimization is a generic population-based metaheuristic that can be adapted to solve a wide variety of optimization problems and has proven very effective for combinatorial optimization problems. However, the potential of this metaheuristic has not been utilized in Distributed Constraint Optimization Problems (DCOPs), a well-known class of combinatorial optimization problems prevalent in Multi-Agent Systems. In this paper, we present a novel population-based algorithm, Anytime Evolutionary DCOP (AED), that uses evolutionary optimization to solve DCOPs. In AED, the agents cooperatively construct an initial set of random solutions and gradually improve them through a new mechanism that considers an optimistic approximation of local benefits. Moreover, we present a new anytime update mechanism for AED that identifies the best among a distributed set of candidate solutions and notifies all the agents when a new best is found. In our theoretical analysis, we prove that AED is anytime. Finally, we present empirical results indicating AED outperforms the state-of-the-art DCOP algorithms in terms of solution quality.Comment: 9 pages, 6 figures, 2 tables. Appeared in the proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2020

    Perancangan Dan Implementasi Augmented Reality Sebagai Media Promosi Penjualan Perumahan

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    Untuk melakukan promosi sebuah Perumahan banyak cara yang dapat dilakukan, misalnya dengan menggunakan brosur yang mana informasinya disampaikan dalam media dua dimensi, maket yang mana informasinya sudah dapat disampaikan dalam media tiga dimensi tetapi harus memerlukan ruang yang tidak sedikit untuk mewujudkannya demi mendapatkan hasil yang maksimal. Yang menjadi masalah disini adalah bagaimana menjadikan suatu informasi tersebut menjadi interaktif dan lebih menarik bagi konsumen. Dengan menggunakan teknik promosi berbasis augmented reality yang dibuat dengan menggunakan ARTool Kit sebagai komponen yang utama dan dengan menggunakan 3DS Max sebagai software untuk menghasilkan gambar yang menarik. Proses perancangan dan pembuatan teknik promosiini akan menggunkan metode waterfall. Kelebihan dari model waterfall adalah struktur tahap pengembangan sistem jelas, dokumentasi dihasilkan disetiap tahap pengembangan, dan sebuah tahap dijalankan setelah tahap sebelumnya selesai dijalankan (tidak ada tumpang tindih pelaksanaan tahap). Hasil dari perancangan aplikasi ini adalah terealisasinya suatu aplikasi untuk kepentingan promosipenjualan Perumahan yang lebih menarik dan interaktif dengan konsumen berbasis augmented reality. Dengan adanya aplikasi ini diharapkan metode promosi dapat berkembang dengan lebih menarik dan tentunya dengan mengandalkan teknologitanpa membutuhkan ruang yang banyak untuk mencapai hasil yang maksimal

    Oseltamivir resistance during treatment of influenza A (H5N1) infection

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    Influenza A (H5N1) virus with an amino acid substitution in neuraminidase conferring high-level resistance to oseltamivir was isolated from two of eight Vietnamese patients during oseltamivir treatment. Both patients died of influenza A (H5N1) virus infection, despite early initiation of treatment in one patient. Surviving patients had rapid declines in the viral load to undetectable levels during treatment. These observations suggest that resistance can emerge during the currently recommended regimen of oseltamivir therapy and may be associated with clinical deterioration and that the strategy for the treatment of influenza A (H5N1) virus infection should include additional antiviral agents. Copyright © 2005 Massachusetts Medical Society.published_or_final_versio
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