5916 research outputs found
Sort by
Otomatikleştirilmiş ikili pazarlıklarda ilişkisel ve frekansçı rakip modelleme yaklaşımları
No full textThis thesis mainly focuses on the problem of learning opponent's preferences during the negotiation in bilateral automated negotiation in which agents negotiate with each other to reach an agreement. Accordingly, it addresses the problems with the classical frequentist approach and advances the state-of-the-art in opponent modeling in automated negotiation by introducing a novel frequency opponent modeling mechanism, which updates some of the assumptions introduced by classical frequency approaches. Moreover, this thesis also proposes adopting association rule mining techniques to learn the opponent's preferences in bilateral negotiation. An extensive evaluation of those proposed approaches shows that the proposed approaches outperform the classical frequency model. In addition, this thesis argues that while optimizing one's utility function is essential, agents in a society should not ignore the opponent's utility in the final agreement to improve the agent's long-term interests in the system. It aims to show whether or not it is possible to design a social agent (i.e., one that aims to optimize both sides' utility functions) while performing efficiently in an agent society. Accordingly, we propose a social agent supported by a portfolio of strategies, a novel tit-for-tat concession mechanism, and a frequency-based opponent modeling mechanism capable of adapting its behavior according to the opponent's behavior and the state of the negotiation. The results show that the proposed social agent does not only maximize social metrics such as the distance to the Nash bargaining point or the Kalai point but also is shown to be a pure and mixed equilibrium strategy in some realistic agent societies.Bu tez esas olarak, etmenlerin bir anlaşmaya varmak için birbirleriyle pazarlık yaptığı otomatikleştirilmiş ikili pazarlık sırasında rakibin tercihlerini öğrenme sorununa odaklanmaktadır. Buna göre, klasik frekansa dayalı yaklaşımla ilgili sorunları ele alır ve klasik frekans yaklaşımlarının getirdiği bazı varsayımların güncellendiği yeni bir frekansa dayalı rakip modelleme mekanizması sunarak, otomatik pazarlıkta alanında rakip modellemede literatürdeki güncel çalışmaları ileri taşır. Ayrıca bu tez, ikili müzakerede rakibin tercihlerini öğrenmek için birliktelik kuralları madenciliği tekniklerinin uygulanmasını önermektedir. Önerilen bu yaklaşım ların kapsamlı bir değerlendirmesi, önerilen yaklaşımların klasik frekans modelinden daha iyi performans gösterdiğini göstermektedir. Buna ek olarak, bu tez aynı zamanda kişinin fayda fonksiyonunu optimize etmenin gerekli olduğunu, ancak bir toplumdaki etmenlerin sistemdeki uzun vadeli çıkarlarını iyileştirmek için nihai anlaşmada rakibin faydasını göz ardı etmemesi gerektiğini savunur. Bir etmen toplumunda verimli bir şekilde performans gösteren (yani her iki tarafın fayda fonksiyonlarını optimize etmeyi amaçlayan) bir sosyal etmen tasarlamanın mümkün olup olmadığını göstermeyi amaçlar. Buna göre, bir strateji portföyü, yeni bir kısasa kısas ödün mekanizması ve davranışını rakibin davranışına ve müzakerenin durumuna göre uyarlayabilen frekansa dayalı bir rakip modelleme mekanizması tarafından desteklenen bir sosyal etmen önerilmektedir. Sonuçlar, önerilen sosyal etmenin yalnızca Nash pazarlık noktasına veya Kalai noktasına olan uzaklık gibi sosyal ölçütleri maksimize etmediğini, aynı zamanda bazı gerçekçi sosyal etmen toplumlarında saf ve karma bir denge stratejisi olduğu da gösterilmiştir
Motor kontrol ve beynin bilişsel karar verme mekanizmalarını analiz etmek üzere tersine pekiştirmeli öğrenme ile keşifler
No full textReinforcement Learning is a framework for generating optimal policies given a task and a reward/punishment structure. Likewise, Inverse Reinforcement Learning, as the name suggests, is used for recovering the reasoning behind an optimal policy based on demonstrations from an expert. We set out to explore whether recent Reinforcement Learning and Inverse Reinforcement Learning methods can serve as a computational tool for investigating optimality principles of motor control and cognitive decision-making mechanisms of the brain. For this purpose, we have targeted several different tasks involved with different parts of the sensorimotor learning mechanism of the brain. We aim to recover the optimality principles employed by the brain for various control and decision-making tasks. If this is achieved, we can analyze, understand, mimic and improve demonstrated behavior with less bias, which we hope is a step forward in understanding the process of learning in both human-based and artificial systems. For the scope of this thesis, we have evaluated two tasks. The first task was investigating the applicability of perceptual development for Reinforcement Learning. For this task, we have proposed a perceptual development based learning regime for a Reinforcement Learning agent, and the results obtained suggest that a suitable perceptual development regime may improve the learning progress and yield better-performing agents. The second task was to predict reward function parameters of a provided trajectory in a standing up under perturbation scenario. For this task, we have proposed two different Inverse Reinforcement Learning approaches. Our results indicate that we were able to infer valid reward parameters on synthetic data.Pekiştirmeli öğrenme, farklı ortamlarda, verilen ödül ceza yapısına göre en uygun politikaları bulma sistemidir. Benzer şekilde, Tersine Pekiştirmeli Öğrenme de, adından anlaşılabileceği gibi, bir uzmandan alınan en uygun politikanın arkasındaki sebepleri bulmak için kullanılır. Bu araştırmada, güncel Pekiştirmeli Öğrenme ve Tersine Pekiştirmeli Öğrenme metotlarının, beynin motor kontrol ve bilişsel karar alma mekanizmalarının arkasındaki eniyileme prensiplerini modelleyen araçlar olarak kullanılabilmesini keşfetmeyi amaçlıyoruz. Bu amaç için, beynin farklı duyusal motor özelliklerini hedefleyen farklı görevleri hedefledik. Niyetimiz, beyin tarafından farklı alanlar için oluşturulan en iyileme kriterlerini keşfedebilmek. Bu başarılabildiği takdirde, varolan veya yeni bir metot ile, insan davranışlarını daha düşük bir yanlılık ile analiz edebilir, anlayabilir ve taklit edebiliriz. Bu tezin kapsamı doğrultusunda, iki tane görevi hedefledik. İlk görev, algısal gelişimin Pekiştirmeli Öğrenme'ye uygulanabilirliğinin araştırılmasıdır. Bu görev için, bir Pekiştirmeli Öğrenme ajanı, kendi önerdiğimiz bir algısal gelişim tabanlı gelişimsel rejim ile eğittik. Sonuçlarımız, uygun bir algısal gelişim rejiminin, Pekiştirmeli Öğrenme'nin öğrenme ilerlemesini geliştirebileceğini ve daha iyi ajanlar üretebileceğini önerdi. İkinci görev ise, Tersine Pekiştirmeli Öğrenme ile, uzmanların ödül fonksiyonu parametrelerini keşfetmekti. Bunun için, iki tane farklı Tersine Pekiştirmeli Öğrenme mekanizması oluşturduk ve sonuçlarımız geçerli ödül fonksiyonu parametreleri keşfettiğimizi önermektedir
Next-day operating room scheduling with time-dependent stochastic surgery durations
No full textOperating rooms (ORs) are the most costly part of hospitals, thus a priority for hospital administrations. In this paper, we consider the next-day OR scheduling problem for multiple operating rooms. We assume that surgeries have uncertain durations, and distributions of surgery durations are time-dependent. Our aim is to find the assignment of surgeries to the available ORs, the sequence, and the planned starting times of surgeries in order to minimize the weighted sum of expected waiting time of patients, idle time of ORs, and overtime of the hospital staff. In order to find solutions to the problem, we propose an L-Shaped method, customized to our problem formulation. We quantify the penalty of ignoring the time-dependency of surgery durations within a numerical study. We find that the penalty of ignoring the time-dependency increases with the overtime cost, average surgery durations, and decreases with surgery variability.TÜBİTA
Renewable energy market incentives under the influence of climate change and sustainability
No full textBugün küresel anlamda enerji talebinin büyük çoğunluğu fosil enerji kaynaklarından karşılanmaktadır. İklim değişikliği sorunun küresel bir krize dönüşmüş olması ve bu durumun sürdürülebilirlik üzerinde büyük tehlike oluşturuyor oluşu ve yine mevcut petrol, doğalgaz, kömür gibi fosil enerji kaynaklarının çevreye zararı ile gelecekteki belirsizliği, çözüm için tek yolun yenilenebilir enerji kaynaklarına yönelmek olduğu gerçeğini karşımıza çıkarmaktadır. İklim krizi ile mücadelede ve sürdürülebilir bir ekonomi ve çevre için yenilenebilir enerji kaynaklarından enerji ve ısı üretiminin hayati olduğu artık tüm dünya tarafından kabul görmektedir. Bu eksende ülkeler gerek ekonomik büyümelerinin devamı, gerekse de dışa bağımlılıklarını azaltmak ve en önemlisi sürdürülebilirlik için iklim krizi ile mücadele edebilmek adına yenilenebilir enerji kaynaklarını teşvik edici uygulamalar kullanmaktadırlar. Bu çalışmanın amacı, Türkiye'de ve Avrupa Birliği'nde seçilmiş bazı ülkeler ile Birleşik Krallık özelinde yenilenebilir enerji yatırımlarına yönelik teşviklerin incelenerek, ülkelerin iklim değişikliği ile mücadele ve sürdürülebilir bir gelecek için uyguladıkları teşvik model ve çeşitlerini ortaya koymaktır.Today, substantial part of the global energy demand is met with fossil energy resources. Focusing on renewable energy resources appears to be the only way for solution considering that climate change turned into a global crisis, the great risk this situation creates on sustainability and environmental damages of and uncertainties about the future of the existing fossil energy resources such as oil, natural gas and coal. There is now consensus around the globe about the fact that generation of energy and heat with renewable energy resources is of vital importance for combatting the climate crisis and ensuring a sustainable economy. For this purpose, countries adopt incentive policies for maintaining the economic growth, encouraging to renewable energy resources, reducing external dependence and more importantly, combatting the climate crisis. The objective of this study is to analyze renewable energy incentives in Turkey, selected European Union member states and the United Kingdom, and describe models and types of incentives implemented by these countries for in order to combat the climate change and for a sustainable future
Hizmet olarak işlev mimarilerinde fiyatlandırma optimizasyonu
No full textCost in Function-as-a-Service computing is influenced by a number of factors. One of these factors is the amount of memory reserved during the deployment of serverless functions. Reservation of an excessive amount increases costs unnecessarily. On the other hand, decreasing this amount increases the function execution time, which is also a factor that contributes to cost. Moreover, insufficient memory can degrade the quality of service. In this thesis, we propose an automated approach for optimizing the amount of memory to be reserved for serverless functions. First, we measure the running time of a given function in various memory settings and derive a regression model. We define an objective function and a set of constraints based on this regres- sion model and the configuration space. We obtain a nonlinear integer programming model, which is solved to determine the optimal memory setting for minimizing cost. We evaluate our approach with an industrial case study on the use of Amazon Web services in the context of Smart Home applications. We show that our approach is effective in accurately estimating the impact of memory settings on runtime perfor- mance and determining optimal settings leading to significant cost reductions. It is also useful in detecting functions with performance issues.Hizmet olarak işlev (Function-as-a-Service) mimarilerinde fiyatlandırma bir çok faktör hesaba katılarak yapılmaktadır. Bu faktörlerden birisi, bir bulut servis sağlayıcıya konuşlandırılan işlev için ayrılacak olan hafıza miktarıdır. Hafıza miktarının yüksek seçilmesi fiyatlandırmayı gereksiz arttıracaktır. Diğer yandan hafızanın düşük seçilmesi fiyatlandırmada rol oynayan diğer bir faktör olan çalışma süresini arttıracaktır. Ayrıca, yetersiz hafıza miktarı işlevin kalitesini de düşürecektir. Bu tez çalışmasında, sunucusuz işlevler için ayrılan hafıza miktarını otomatik olarak eniyileyen bir yaklaşım sunulmaktadır. İlk olarak söz konusu işlevin farklı hafıza değelerindeki performans ölçümleri kullanılarak bir regresyon modeli oluşturulmaktadır. Konfigürasyon uzayı ve regresyon modeli kullanılarak amaç fonksiyonu ve kısıtları belirlenmektedir. Bu verileri kullanarak elde edilen doğrusal olmayan programlama modelininin çözümü ise seçilmesi gereken en iyi hafıza miktarını vermektedir. Önerilen yaklaşımı değerlendir-mek için Amazon Web hizmetlerinin kullanıldığı bir Akıllı Ev Sistemleri Bulut Uygulaması kullanılmıştır. Önerilen yaklaşım ile işlevlerin çalışma performansları göz önünde bulundurularak en düşük seviyede fiyatlandırma ve istenen kaliteyi sağlayacak hafıza seçimlerinin yapıldığı görülmüştür. Ayrıca, bu yaklaşımın kullanılması ile bazı işlevlere ilişkin performans problemlerinin de tespit edilebildiği ortaya çıkmıştır
Search for invisible decays of the Higgs boson produced via vector boson fusion in proton-proton collisions at √s = 13 TeV
No full textA search for invisible decays of the Higgs boson produced via vector boson fusion (VBF) has been performed with 101 fb-1 of proton-proton collisions delivered by the LHC at s=13 TeV and collected by the CMS detector in 2017 and 2018. The sensitivity to the VBF production mechanism is enhanced by constructing two analysis categories, one based on missing transverse momentum and a second based on the properties of jets. In addition to control regions with Z and W boson candidate events, a highly populated control region, based on the production of a photon in association with jets, is used to constrain the dominant irreducible background from the invisible decay of a Z boson produced in association with jets. The results of this search are combined with all previous measurements in the VBF topology, based on data collected in 2012 (at s=8 TeV), 2015, and 2016, corresponding to integrated luminosities of 19.7, 2.3, and 36.3 fb-1, respectively. The observed (expected) upper limit on the invisible branching fraction of the Higgs boson is found to be 0.18 (0.10) at the 95% confidence level, assuming the standard model production cross section. The results are also interpreted in the context of Higgs-portal models.BMBWF and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP (Brazil); MES and BNSF (Bulgaria); CERN; CAS, MoST, and NSFC (China); MINCIENCIAS (Colombia); MSES and CSF (Croatia); RIF (Cyprus); SENESCYT (Ecuador); MoER, ERC PUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRI (Greece); NKFIA (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); MES (Latvia); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MOS (Montenegro); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, RosAtom, RAS, RFBR, and NRC KI (Russia); MESTD (Serbia); MCIN/AEI and PCTI (Spain); MOSTR (Sri Lanka); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU (Ukraine); STFC (United Kingdom); DOE and NSF (USA). Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, Grants No. 675440, No. 724704, No. 752730, No. 758316, No. 765710, No. 824093, and No. 884104, and COST Action CA16108 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation `a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie doorWetenschap en Technologie (IWT-Belgium); the F. R. S.-FNRS and FWO (Belgium) under the "Excellence of ScienceEOS"-be.h Project No. 30820817; the Beijing Municipal Science & Technology Commission, Grant No. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Deutsche Forschungsgemeinschaft (DFG), under Germany's Excellence Strategy-EXC 2121 "Quantum Universe"-Grant No. 390833306, and under Project No. 400140256-GRK2497; the Lendulet ("Momentum") Program and the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program UNKP, the NKFIA research Grants No. 123842, No. 123959, No. 124845, No. 124850, No. 125105, No. 128713, No. 128786, and No. 129058 (Hungary); the Council of Science and Industrial Research, India; the Latvian Council of Science; the Ministry of Science and Higher Education and the National Science Center, Contracts Opus 2014/15/B/ST2/03998 and 2015/19/B/ST2/02861 (Poland); the Fundacao para a Ciencia e a Tecnologia, Grant No. CEECIND/01334/2018 (Portugal); the National Priorities Research Program by Qatar National Research Fund; the Ministry of Science and Higher Education, Projects No. 0723-2020-0041 and No. FSWW-20200008, and the Russian Foundation for Basic Research, Project No. 19-42-703014 (Russia); Grant No. MCIN/AEI/10.
13039/501100011033, ERDF "a way of making Europe," and the Programa Estatal de Fomento de la Investigacion Cientifica y T ' ecnica de Excelencia Maria de Maeztu, Grant No. MDM-2017-0765, and Programa Severo Ochoa del Principado de Asturias (Spain); the Stavros Niarchos Foundation (Greece); the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University, and the Chulalongkorn Academic into its 2nd Century Project Advancement Project (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, Contract No. C-1845; and the Weston Havens Foundation (USA).Publisher versio
Pool boiling heat transfer in dielectric fluids and impact of surfaces on the repeatability
No full textThis study presents an experimental investigation on the nucleate boiling heat transfer (NBHT) in deionized (DI) water and HFE-7100 on bare copper surfaces. The experiments were performed under atmospheric condition at 0 and 10 K subcooling levels. The primary objective was to understand the effect of fluid property on critical heat flux (CHF) and heat transfer performance, where the occurrence of surface oxidation over the entire set of experiments were investigated for a range of operating conditions. In order to determine the onset and development of the latter phenomenon, experiments for the complete boiling process have been repeated three times under similar conditions. A detailed visualization study with a highspeed camera has been utilized to capture the dynamics of bubble formation and departure. Additionally, high-resolution microscopic images were captured, and contact angle measurements were used to express the experimental results conveniently. Microscopic images showed that using DI water leads to an intensified oxidization on the heater surface, while HFE-7100 yields a minor occurrence of oxide layer on the copper surfaces. The results indicated that CHF values remain constant for water at 0 K; however, a remarkable increase was observed for 10 K subcooling from the first to third run of successive measurements.Ozyegin University ; Deutsche Forschungsgemeinschaf
Cost of fairness in agent scheduling for contact centers
No full textWe study a workforce scheduling problem faced in contact centers with considerations on a fair distribution of shifts in compliance with agentpreferences. We develop a mathematical model that aims to minimize operatingcosts associated with labor, transportation of agents, and lost customers.Aside from typical work hour-related constraints, we also try to conform withagents' preferences for shifts, as a measure of fairness. We plot the trade-off between agent satisfaction and total operating costs for Vestel, one of Turkey'slargest consumer electronics companies. We present insights on the increasedcost to have content and a fair environment on several agent availability scenarios
Speaking but not gesturing predicts event memory: a cross-linguistic comparison
No full textEvery day people see, describe, and remember motion events. However, the relation between multimodal encoding of motion events in speech and gesture, and memory is not yet fully understood. Moreover, whether language typology modulates this relation remains to be tested. This study investigates whether the type of motion event information (path or manner) mentioned in speech and gesture predicts which information is remembered and whether this varies across speakers of typologically different languages. Dutch- and Turkish-speakers watched and described motion events and completed a surprise recognition memory task. For both Dutch- and Turkish-speakers, manner memory was at chance level. Participants who mentioned path in speech during encoding were more accurate at detecting changes to the path in the memory task. The relation between mentioning path in speech and path memory did not vary cross-linguistically. Finally, the co-speech gesture did not predict memory above mentioning path in speech. These findings suggest that how speakers describe a motion event in speech is more important than the typology of the speakers' native language in predicting motion event memory. The motion event videos are available for download for future research at https://osf.io/p8cas/.Nederlandse Organisatie voor Wetenschappelijk OnderzoekPublisher versio
Robust strategic planning of dynamic wireless charging infrastructure for electric buses
No full textElectromobility in public bus systems is growing rapidly and experiencing a fundamental transformation in their infrastructure and operations. The dilemma of limited driving range and charging time of battery electric buses (BEBs) hinders their adoption. A novel approach to address BEB limitations is to utilize dynamic wireless charging (DWC) technology that allows buses to charge while in motion. This paper aims to analyze robust strategic planning of DWC and BEB fleet scheduling based on a real bus network at Binghamton University. The problem is first formulated as a new deterministic mixed-integer linear programming model to simultaneously optimize both the charging planning problem and fleet scheduling problem in an integrated fashion. To address the uncertainty of energy demand and charging time, a robust counterpart model (RCM) has been derived. To increase RCM flexibility, the battery status variable is formulated in a cumulative form. Dependent and independent budget uncertainty sets have been developed to control the robustness. A sensitivity analysis has been conducted to study the system behavior in response to different charging types, auxiliary energy demand, depth of discharge, charging options at terminals, battery degradation, and electricity cost. The deterministic model shows that eight homogeneous BEBs are required to operate on the selected routes with a battery capacity of 54.01 kWh and a total cost of $3,636,347. The results show that joint planning of charging infrastructure and fleet scheduling can save 19.2% of total cost compared to disjoint planning. The RCM results in 10 BEBs to ensure feasiblility against uncertainty