Machine Learning Approach for Optimizing Negotiation Agents

The increasing popularity of Internet and World Wide Web (WWW) fuels the rise of electronic commerce (E-Commerce). Negotiation plays an important role in ecommerce as business deals are often made through some kind of negotiations. Negotiation is the process of resolving conflicts among parties having different criteria so that they can reach an agreement in which all their constraints are satisfied. Automating negotiation can save human’s time and effort to solve these combinatorial problems. Intelligent Trading Agency (ITA) is an automated agentbased one-to-many negotiation framework which is incorporated by several one-toone negotiations. ITA uses constraint satisfaction approach to evaluate and generate offers during the negotiation. This one-to-many negotiation model in e-commerce retail has advantages in terms of customizability, scalability, reusability and robustness. Since negotiation agents practice predefined negotiation strategies, decisions of the agents to select the best course of action do not take the dynamics of negotiation into consideration. The lack of knowledge capturing between agents during the negotiation causes the inefficiency of negotiation while the final outcomes obtained are probably sub-optimal. The objective of this research is to implement machine learning approach that allows agents to reuse their negotiation experience to improve the final outcomes of one-to-many negotiation. The preliminary research on automated negotiation agents utilizes case-based reasoning, Bayesian learning and evolutionary approach to learn the negotiation. The geneticbased and Bayesian learning model of multi-attribute one-to-many negotiation, namely GA Improved-ITA and Bayes Improved-ITA are proposed. In these models, agents learn the negotiation by capturing their opponent’s preferences and constraints. The two models are tested in randomly generated negotiation problems to observe their performance in negotiation learning. The learnability of GA Improved-ITA enables the agents to identify their opponent’s preferable negotiation issues. Bayes Improved-ITA agents model their opponent’s utility structure by employing Bayesian belief updating process. Results from the experimental work indicate that it is promising to employ machine learning approach in negotiation problems. GA Improved-ITA and Bayes Improved-ITA have achieved better performance in terms of negotiation payoff, negotiation cost and justification of negotiation decision in comparison with ITA. The joint utility of GA Improved-ITA and Bayes Improved-ITA is 137.5% and 125% higher than the joint utility of ITA while the negotiation cost of GA Improved-ITA is 28.6% lower than ITA. The negotiation successful rate of GA Improved-ITA and Bayes Improved-ITA is 10.2% and 37.12% higher than ITA. By having knowledge of opponent’s preferences and constraints, negotiation agents can obtain more optimal outcomes. As a conclusion, the adaptive nature of agents will increase the fitness of autonomous agents in the dynamic electronic market rather than practicing the sophisticated negotiation strategies. As future work, the GA and Bayes Improved-ITA can be integrated with grid concept to allocate and acquire resource among cross-platform agents during negotiation

Info Kampus Isu 9-Nov 2001 / UiTM Cawangan Sarawak

Seramai 647 siswa/siswi baru telah mendaftar diri sebagai warga baru UiTM Cawangan Sarawak pada 4 Nov 2001. selepas pendaftaran Kolej dan Akademik selesai, sebagaimana lazim, siswa/siswi baru menjalani Minggu nWawasan Siswa (MWS) untuk menyesuaikan diri dalam msuasana kehidupan dalam kampus. walau bagaimanapun, tidak seperti Minggu Wawasan Siswa terdahulu, MWS kali ini hanya dijalankan untuk tempoh tiga hari iaitu dari 4 Nov sehingga 6 Nov untuk mematuhi arahan dari Kementerian Pendidikan. Siswa/siswi baru perlu mengikuti 'Academic Enhancement Program' dari 7 Nov hingga 9 Nov

Info Kampus UiTM Sarawak Isu 45 / Universiti Teknologi MARA

I am glad to be back among old friends anti at the same time eager to get to know those that I have not met yet. I am also well aware of the excellent work alone here by everyone under the able leadership of Prof Dr Abdul Rahman Deen who, as a matter of fact has been a great influence on my own personal and professional development. I sincerely hope that I will get the same quality of support enjoyed by Prof Dr Rahman so that we can proceed with our agenda of achieving the mission anti vision formulated by our honourable Vice-Chancellor. And thank you for the war m reception

Pencetusan idea reka bentuk produk mengguna TRIZ

Kemajuan teknologi pada era globalisasi adalah menakjubkan. Sektor industri tidak ketinggalan mengguna teknologi bagi mereka bentuk produk untuk kegunaan pengguna. Dalam mereka bentuk sesuatu produk, pereka bentuk dalam industri perlu mengenal pasti idea yang diperlu untuk menyelesai masalah yang dihadapi oleh pengguna terlebih dahulu sebelum menghasil reka bentuk sebenar. Pada kebiasaannya idea dicetus secara bebas dan pendekatan sistematik jarang diguna. TRIZ banyak diguna oleh industri yang berjenama popular seperti Samsung, Christian Dior dan Procter & Gamble untuk menghasil produk yang bersaing tinggi. Justeru, kaedah pencetusan idea yang sistematik perlu diterokai dan dieksploitasi sepenuhnya. Makalah ini membincang satu kaedah pencetusan idea sistematik yang dikenali sebagai TRIZ yang boleh menyelesai masalah reka bentuk produk pengguna

Focus Group Interview as a Means to Determine School Effectiveness Indicators / Sueb Ibrahim ...[et al.]

The growth of interest in school effectiveness has been striking and is gaining momentum. Similarly in Malaysia, school effectiveness has become a dominant theme in contemporary educational reform and development. Thus, the growing concern about educational reform has resulted in a wide variety of school effectiveness interventions, initiatives and strategies. Although school effectiveness has become the central focus in most schools, there is still a strong need to determine the constructs or dimensions that are suitable to measure school effectiveness in Malaysian secondary schools. In this study, a focus group interview consisting of eight selected excellent and senior school principals were conducted. The findings from the focus group interview indicated 5 indicators for school effectiveness which comprised academic performance, school programme, organizational effectiveness, learning environment and school achievement. The findings also indicated 15sub-indicators for school effectiveness consisting of curriculum, public exam, student assessment, academic programme, co-curriculum programme, student development, resource management, technology advancement, data and information management, teaching and learning, community relation, staff professional development,, award and recognition, innovation and niche are

Info Kampus UITM Cawangan Sarawak isu 44-feb 05

Assalammualaikum w.b.t dan salam sejahtera.Terlebih dahulu saya bagi pihak warga kampus Uitm Cawangan Sarawak mengucapkan tahniah kepada Pengarah Kampus atas penganugerahan pangkat profesor.Kami semua mendoakan agar Prof sentiasa maju jaya

Ultrasonic NDE for internal defect detection in multi-layered composite materials by multi-resolution signal decomposition

Ultrasonic NDE has been a well known approach to investigate material’s microstructures, mechanical properties and structure integrity in industry. The internal structure of a material and position of anomalies can be recognised by the reactions of different materials to ultrasound. However, the interpretation of ultrasound signals is difficult in composite material inspection task due to the fact that the ultrasonic pulse is reflected not only by the defect occurred within the material but the microstructures and multiple lay ups of the material. This phenomenon causes the backscattering noise to hinder the real defect’s signal during the inspection. Backscattering noise exists in multiple frequencies. The objective of this study was to develop a new noise reduction method to enhance the defect detectability in coarse-grained structure material such as composites materials. This method increases Signal-to-noise Ratio (SNR) by means of decomposing the original signal into multiresolution representations. To prevent the loss of information, the signal is processed in both temporal and frequency domain. The proposed method has been tested on simulated signal and Glass Fiber Reinforced Plastics (GFRP) laminates. Both simulation and experimental results showed that this method can significantly reduce grain noise while preserving the resolution of the original signal of the defect

Penjanaan reka bentuk produk dengan nahu bentuk

Nahu bentuk adalah kaedah formal yang berkenaan dengan bentuk. Unsur dalam nahu bentuk adalah bentuk, label dan peraturan. Nahu bentuk selalu diguna untuk menganalisis dan menjana reka bentuk dalam pelbagai bidang termasuk seni lukis, seni bina, kejuruteraan dan produk konsumer bagi mengekal gaya dan struktur tertentu. Nahu bentuk yang mengguna konsep ruang, bentuk yang boleh berurai dan ketaksaan aplikasi peraturan bentuk dapat menghasil reka bentuk yang muncul secara tidak terjangka. Artikel ini memperkenal nahu bentuk dengan mengguna nahu bentuk kekisi sinar-ais dan dua contoh nahu bentuk daripada sorotan susastera bagi menunjukkan konsep kemunculan dan ketaksaan. Artikel ini diakhiri dengan kajian kes penjanaan reka bentuk meja mudah alih berkerusi dengan mengguna satu nahu bentuk mudah

Retrieval System for Patent Images

AbstractPatent information and images play important roles to describe the novelty of an invention. However, current patent collections do not support image retrieval and patent images are become almost unsearchable. This paper presents a short review of the existing research work and challenges in patent image retrieval domain. From the review, the image feature extraction step is found to be an important step to match the query and database images successfully. In order to improve the current feature extraction step in image patent retrieval, we propose a patent image retrieval approach based on Affine-SIFT technique. Comparison discussions between the existing feature extraction techniques are presented to assess the potential of this proposed approach