مولوی احتشام علی ندوی
افسوس ہے کہ ۲۰؍ رمضان المبارک کو مولوی احتشام علی ندوی اچانک چل بسے، ان کی تعلیم دارالعلوم ندوۃ العلماء میں ہوئی، وہ مولانا عبدالسلام قدوائی ندوی مرحوم کے چہیتے شاگردوں میں تھے، انہی کے ایما سے جامعہ ملیہ میں داخلہ لیا، مولانا عبدالسلام صاحب نے لکھنؤ میں ادارۂ تعلیمات اسلام کی داغ بیل ڈالی تو اس کی تشکیل میں یہ بھی ان کے معاون رہے اور ان کی نگرانی میں صحابہ کرام کے حالات میں مختصر اور عام فہم بعض کتابچے لکھے۔
دارالمصنفین سے ان کا تعلق دو بار رہا، پہلی دفعہ وہ مولانا عبدالسلام قدوائی کے ساتھ آئے اور محاسب کی ذمہ داری سنبھالی، ان کے انتقال کے بعد انہوں نے بھی یہاں سے تعلق منقطع کرلیا، تاہم دارالمصنفین سے ان کے لگاؤ میں کمی نہیں آئی جناب سید صباح الدین صاحب مرحوم کے انتقال کے بعد پھر وہ دارالمصنفین تشریف لائے اور پریس کی نگرانی اور دوسرے انتظامی امور ان کو سپرد کئے گئے لیکن اس دفعہ ان کی صحت خراب رہنے لگی۔ دو تین برس سے کمزوری بہت بڑھ گئی تھی اور ضعف بصر کی شکایت بھی ہوگئی تھی۔ ان کا انتقال دارالمصنفین ہی میں ہوا، مگر تدفین ان کے وطن رحیم آباد میں ہوئی۔ اﷲ تعالیٰ درجات بلند کرے اور اہلیہ و اعزہ کو صبرِ جمیل عطا کرے آمین!
(ضیاء الدین اصلاحی، جنوری ۲۰۰۰ء)
Based on the 2013 curriculum 2016’s revision, there are subject materials that demand about local content in English subjects at the level of SMP Class VII. Teachers need many researches and practices integrating and implementating these subjects. Basically, it needs to be done in-depth study in the form of content analysis. This research was conducted on content and learning English in SMP Negeri 5 Sigi. This study aims to find out 1) how many percentage of local content in English lesson material Class VII SMP in the curriculum 2013 revision 2016; 2) how to integrate local content in English subject matter in SMP Negeri 5 Sigi; 3) how the implementation of material with local content in English learning in SMP Negeri 5 Sigi, and; 4) how to integrate local content in effective and efficient English lessons in SMP Negeri 5 Sigi. The study used a qualitative descriptive approach with the method of collecting document studies, interviews, and observation. The research results are 1) the proportion of local content that can be integrated into English language learning material SMP is 95%; 2) the integrity of local content in English learning materials in SMP Negeri 5 Sigi can be found in the lesson plan; 3) implementation of materials with local content in English learning attached to KTSP, Syllabus, lesson plan and learning resources enrichment book.
This dissertation addresses the problem of building collaboration in a team of autonomous agents and presents imitation learning as an effective mechanism to build this collaboration. Imitation learning involves learning from an expert by observing her demonstrating a task and then mimicking her. This mechanism requires less time and technical expertise on behalf of domain experts/ knowledge engineers and makes it convenient for them to transfer knowledge to a software agent. The research extends the idea of a demonstration to multi-human demonstrations and presents a framework of Team Learning from Demonstration (TLfD) that allows a group of human experts to train a team of agents via demonstrations. A major challenge faced by the research is to cope with the overhead of demonstrations and inconsistencies in human demonstrations. To reduce the demonstration overhead, the dissertation emphasizes on a modular approach and enables the framework to train a team of a large number of agents via smaller numbers of demonstrators. The framework learns the collaborative strategy in the form of weighted naïve Bayes model where the parameters of the model are learned from the demonstration data and its weights are optimized using Artificial Immune Systems. The framework is thoroughly evaluated in the domain of RoboCup Soccer Simulation 3D which is a promising platform for a multi-agent domain and addresses many complex real-world problems. A series of experiments were conducted using RoboCup Soccer in which the agents were trained to perform different types of tasks through TLfD framework. The experiments were started with training a single agent how to score a goal in an empty soccer field. The later experiments increased the complexity of the task and the number of agents involved. The final experiment eventually trained a full-fledged team of nine soccer players and enabled them to play soccer against other competition quality teams. A number of test matches were played against different opponent teams, and the results of the matches were evaluated on the basis of different performance and behavioral metrics. The performance metrics described how well the imitating team played in the field whereas the behavioral metrics assessed how closely they had imitated the human demonstrations. Our soccer simulation 3D team KarachiKoalas served as a benchmark to evaluate the quality of the imitating team, and the dissertation closely compared the two teams and found that the team that was trained via imitation gave comparable performance to KarachiKoalas. The results showed the effectiveness of TLfD framework and supported the idea of using imitation to build collaboration among multiple agents. However, the framework, in its current form, does not support strategy building in an incremental manner in which a naïve strategy is learned via imitation and is refined in stages. The ability to build strategies incrementally can be a crucial requirement in complex systems. In future, the framework can be extended to incorporate the ability to refine an already learned strategy via human expert’s feedback.