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You look nice, but i am here to negotiate: The influence of robot appearance on negotiation dynamics
No full textThis report presents two experimental studies examining whether relatively subtle differences in the appearances of humanoid robots impact (1) the outcomes of human-robot negotiation (i.e., utility scores) and (2) the participant's attitudes toward their robot negotiation partner. Study I compared Nao and Pepper, and Study II compared Nao and QT in identical negotiation settings. While the appearance of robots influenced the participant's attitudes toward the robot before and after the negotiation, such differences were not manifested in the utility scores. The consistent utility scores across different robots reassure that minor variations in the visual characteristics of robots do not alter how users negotiate with a robot. Yet, as participants felt differently about the three robots, there remains the possibility that the differences in their appearances may influence the user's initial inclination to approach each robot. As among the first to systematically investigate the influence of robot appearance on human-robot negotiations, this study emphasizes the importance of assessing both objective outcome scores and the subjective experience of the user in human-robot interaction (HRI) research and offers valuable insights for designing and implementing social robots in real-world settings including customer service and other AI-based interactions.TÜBİTA
İkili müzakerelerde zaman serisi tahmin modelleri.
No full textThis thesis explores the dynamics of agent-based negotiations, with a focus on understanding opponent's behavior and predicting their offering patterns to make strategic decisions. Guessing the utility of the opponent's upcoming offers valuable insights for the agent's subsequent moves. The research aims to predict the opponent's future offers by employing diverse learning algorithms in various situations to measure their effectiveness in comprehending negotiation behavior. The prediction study comprises two parts; one investigating the impact of these models in one-to-one negotiations, specifically tailored for the agent's own experiences, while the other examines the performance of predictive models in a tournament setting for all agents. A learning process with three distinct targets have been established to assess the prediction models: (i) estimating the agent's utility of the opponent's next offer by considering only its offer history, (ii) estimating the agent's utility considering opponent-related variables, and (iii) estimating the opponent's utility using opponent-related variables. According to the experimented results, the best learning approach is incorporated into an agent design to observe the impacts of having predictions of future utility values on the agent's negotiation success. The thesis evaluates these models in diverse negotiation scenarios and highlights promising outcomes for the proposed methods. It also introduces a novel negotiation strategy called `Negoformer', which incorporates predictions into the offering strategy and investigates their impact on the outcome of negotiations. The experiments showcased the success of Negoformer compared to other agents in various negotiation success metrics, such as individual utility value and social welfare score.Bu tez, etmen tabanlı müzakerelerin dinamiklerini araştırırken rakip etmenlerin davra- nışlarını anlama ve stratejik kararlar almak için teklif örüntülerini tahmin etmeye odaklanır. Rakibin gelecekteki tekliflerinin faydasını tahmin etmek, etmenin sonraki hamleleri için değerli içgörüler sunmaktadır. Araştırma, etmen davranışlarını anlama yetkinliğini ölçmek için çeşitli öğrenme algoritmalarını kullanarak rakibin gelecekteki tekliflerini tahmin etmeyi amaçlamaktadır. Tahminleme becerilerine odaklanan çalışma iki bölümden oluşmaktadır: ilki etmenin kendi deneyimleri baz alınarak tasarlanmış tekli müzakerelerde bu modellerin etkisini incelemekteyken diğeri turnuva boyunca tüm etmenler için tahmin modellerinin performansını incelemektedir. Tahmin modellerini değerlendirmek için üç farklı hedefe yönelik bir öğrenme süreci oluşturulmuştur: (i) teklif geçmişinden yararlanarak rakibin bir sonraki teklifinin etmene faydasını tahmin etmek, (ii) rakiple ilgili değişkenleri dikkate alarak etmenin faydasını tahmin etmek, ve (iii) rakiple ilgili değişkenleri kullanarak rakibin faydasını tahmin etmek. Deneylerde gözlemlenen en iyi öğrenme modeli, gelecekteki fayda değerlerini tahmin etmenin etmenlerin müzakere başarısı üzerindeki etkilerini gözlemlemek için etmen tasarımına dahil edilmiştir. Çalışmalar çeşitli müzakere senaryolarında kullanılan bu modellerin değerlendirme sonuçlarını sunarak önerilen metodların umut verici olduğunu ortaya koymaktadır. Ayrıca, müzakere stratejisine tahminleri dahil eden `Negoformer' isimli yeni bir teklif stratejisi sunulmaktadır ve bu stratejinin başarısı otonom müzakere senaryolarında test edilmiştir. Deney sonuçları, Negoformer stratejisinin karşılaştırılan diğer etmenlere göre bireysel fayda ve toplumsal fayda gibi müzakere metriklerinde daha başarılı olduğunu ortaya koymaktadır
A long battle: turkey's backsliding and resistance through trench warfare
No full textSince 2002, governments led by Recep Tayyip Erdo & gbreve;an and his party have taken Turkey's political regime from electoral democracy to electoral autocracy. This has been principally accomplished through legislative capture: control, abuse, and weaponization of Parliament to pass democracy-eroding laws, discredit opposition, and legitimize executive authoritarianism. But other tools, such as executive power grabs, were also used against strong state institutions, civil society, and even by Erdo & gbreve;an against his own party. Democratic backsliding advanced through crises that polarized the electorate and through fierce political warfare between the incumbent government and its opponents. Like other cases on the legislative capture pathway, opposition parties have resisted backsliding predominantly through electoral mobilization, but their partial access to the legislature has, for the most part, limited their capacity to join forces with grassroots contentious politics. The opposition has not developed solutions for programmatic renewal that might heal formative rifts and lead to sustainable recovery
Semi-automated creation of reciprocal frame structures using deep learning
No full textSystems that can transform two-dimensional (2D) sketches into 3D models while performing structural analyses are necessary for architectural sketches. To address this challenge, this paper focuses on how deep-learning algorithms can aid in this transformation process. It presents a model that uses the instance-segmentation technique with Mask RCNN to detect and distinguish two types of short beams of reciprocal frame structures (RFs) in 2D sketches and uses this information in the systematic creation of a 3D model of RFs to conduct their structural analysis. The results indicate that the model is capable of clustering beam types in 2D sketches via masking and classifying, eliminating irrelevant background objects, creating parametric RFs using masking information, and performing structural analysis. The model, which helps optimise and ease the design process, can be used by architects or engineers. This paper will inspire future work on the creation of integrated modelling systems
Expansions in paid parental leave and mothers' economic progress
No full textThis paper investigates the impact of reforms extending paid parental leave on mothers' progress to the upper echelons of their companies. Using employer-employee matched data and examining a series of reforms between 1987 and 2005 in Norway, we find that longer parental leave neither helped nor hurt mothers' chances to be at the top of their companies' pay ranking or in the C-suite up to 25 years after childbirth. This holds true also for highly educated women and high performers across all sectors. Key career determinants, such as hours worked and promotions, are unaffected in the short and long run. Finally, fathers' career progression and within-household gender wage gaps have also remained unaltered.Research Council of NorwayPublisher versio
Enhancement of damping characteristics through hybridization: Investigating the synergistic effects of triply periodic minimal surface additive metals and silicone polymers
No full textUsing triply periodic minimal surface (TPMS) metal parts with added silicone polymer can lead to the development of hybrid materials with enhanced damping characteristics. This study aims to develop composite structures by hybridizing additively manufactured TPMS metal parts with added silicone polymers for vibration applications. Central to this investigation is the quest to ascertain the most efficacious damping mechanism. In this context, the finite element method (FEM)-based model of the primitive TPMS structure, consisting of cobalt–chrome (CoCr) and the concomitant hybrid structure integrated with silicone polymer, is meticulously developed. The damping characteristics of the FEM-based models are obtained by modal analysis. The models are also validated using experimental modal tests. The findings show a significant improvement in damping characteristics thanks to the hybrid TPMS structure. Specifically, the damping ratios derived from the hybrid TPMS structure exhibit a sixfold increase in time-domain damping and up to a 30-fold increase in frequency-based analysis across two distinct damping calculation methodologies. Overall, this study highlights the potential of additively fabricated primitive TPMS metal parts with added silicone polymer as a promising structure for improving damping properties in various engineering applications.Ansys GRANTA Research SelectorPublisher versio
NegoLog: An integrated python-based automated negotiation framework with enhanced assessment components
No full textThe complexity of automated negotiation research calls for dedicated, user-friendly research frameworks that facilitate advanced analytics, comprehensive loggers, visualization tools, and autogenerated domains and preference profiles. This paper introduces NegoLog, a platform that provides advanced and customizable analysis modules to agent developers for exhaustive performance evaluation. NegoLog introduces an automated scenario and tournament generation tool in its Web-based user interface so that the agent developers can adjust the competitiveness and complexity of the negotiations. One of the key novelties of the NegoLog is an individual assessment of preference estimation models independent of the strategies.CHIST-ERA ; Vidi project COMBINE ; TÜBİTAK ; Netherlands Organization for Scientific Research (NWO
On evolution of grain refinement and mechanical properties in Cu/Low-Carbon Steel/Cu composites manufactured by different rolling routes
No full textThe processing of Cu/low-carbon steel/Cu multilayered composites by accumulative double-pass rolling (ADPR) has been studied, and the effect of different rolling directions, including unidirectional, cross, and reverse routes, on the microstructure and mechanical properties has been analyzed. The incorporation of four cycles of the ADPR method resulted in a uniform distribution of low-carbon steel in the Cu matrix. More plastic instabilities appeared by using a unidirectional rolling route, while the fewest instabilities occurred during the cross-rolling route. This shows the enhanced deformability of layers by 90 degrees rotation of the rolling direction. This was also confirmed by a finer ultrafine-grained microstructure and improved tensile and hardness properties. The processed samples by the cross-rolling route demonstrated higher hardness, strengths, and elongation. The highest tensile strength of 663 MPa and highest hardness of 231 HV on the Cu layer and 263 HV on the steel layer were obtained. Moreover, the variations of measured hardness from surface to center of composites were analyzed and showed the maximum value near the surface of the composites
Correspondence learning between morphologically different robots via task demonstrations
No full textWe observe a large variety of robots in terms of their bodies, sensors, and actuators. Given the commonalities in the skill sets, teaching each skill to each different robot independently is inefficient and not scalable when the large variety in the robotic landscape is considered. If we can learn the correspondences between the sensorimotor spaces of different robots, we can expect a skill that is learned in one robot can be more directly and easily transferred to other robots. In this paper, we propose a method to learn correspondences among two or more robots that may have different morphologies. To be specific, besides robots with similar morphologies with different degrees of freedom, we show that a fixed-based manipulator robot with joint control and a differential drive mobile robot can be addressed within the proposed framework. To set up the correspondence among the robots considered, an initial base task is demonstrated to the robots to achieve the same goal. Then, a common latent representation is learned along with the individual robot policies for achieving the goal. After the initial learning stage, the observation of a new task execution by one robot becomes sufficient to generate a latent space representation pertaining to the other robots to achieve the same task. We verified our system in a set of experiments where the correspondence between robots is learned 1) when the robots need to follow the same paths to achieve the same task, 2) when the robots need to follow different trajectories to achieve the same task, and 3) when complexities of the required sensorimotor trajectories are different for the robots. We also provide a proof-of-the-concept realization of correspondence learning between a real manipulator robot and a simulated mobile robot.Japan Society for the Promotion of Scienc
Vectorial bent functions with non-weakly regular components
No full textIt is shown that the generalized Rothaus construction of p-ary bent functions can be extended to a construction of a vectorial bent function with non-weakly regular components, for which in general the duals are not a bent function, i.e., they belong to the class of non-dual bent functions. This complements results on other two constructions of non-weakly regular bent functions, the generalized Maiorana-McFarland construction and the semi-direct sum, for which vectorial versions are presented and the properties of their duals are investigated in the literature. The distribution of the values of the Walsh transform of vectorial bent functions (with non-weakly regular components) is then analysed in detail. Among others, a condition on the values of the Walsh transform of a vectorial bent function from F-p(n) to F-p(m) is presented, which implies that m <= [n/2]. This refines a classical result by Nyberg, which states that for an (n, m) bent function, n even, with only regular components, m can be at most n/2. Some results on the weight distribution of codes obtained from vectorial bent functions with non-weakly regular components complement the article.Austrian Science Fund (FWF