Budget-Feasible Mechanism Design for Non-Monotone Submodular Objectives: Offline and Online

The framework of budget-feasible mechanism design studies procurement auctions where the auctioneer (buyer) aims to maximize his valuation function subject to a hard budget constraint. We study the problem of designing truthful mechanisms that have good approximation guarantees and never pay the participating agents (sellers) more than the budget. We focus on the case of general (non-monotone) submodular valuation functions and derive the first truthful, budget-feasible and $O(1)$-approximate mechanisms that run in polynomial time in the value query model, for both offline and online auctions. Prior to our work, the only $O(1)$-approximation mechanism known for non-monotone submodular objectives required an exponential number of value queries. At the heart of our approach lies a novel greedy algorithm for non-monotone submodular maximization under a knapsack constraint. Our algorithm builds two candidate solutions simultaneously (to achieve a good approximation), yet ensures that agents cannot jump from one solution to the other (to implicitly enforce truthfulness). Ours is the first mechanism for the problem where---crucially---the agents are not ordered with respect to their marginal value per cost. This allows us to appropriately adapt these ideas to the online setting as well. To further illustrate the applicability of our approach, we also consider the case where additional feasibility constraints are present. We obtain $O(p)$-approximation mechanisms for both monotone and non-monotone submodular objectives, when the feasible solutions are independent sets of a $p$-system. With the exception of additive valuation functions, no mechanisms were known for this setting prior to our work. Finally, we provide lower bounds suggesting that, when one cares about non-trivial approximation guarantees in polynomial time, our results are asymptotically best possible.Comment: Accepted to EC 201

Budget-feasible mechanism design for non-monotone submodular objectives: Offline and online

The framework of budget-feasible mechanism design studies procurement auctions where the auctioneer (buyer) aims to maximize his valuation function subject to a hard budget constraint. We study the problem of designing truthful mechanisms that have good approximation guarantees and never pay the participating agents (sellers) more than the budget. We focus on the case of general (non-monotone) submodular valuation functions and derive the first truthful, budget-feasible and O(1)-approximation mechanisms that run in polynomial time in the value query model, for both offline and online auctions. Since the introduction of the problem by Singer [40], obtaining efficient mechanisms for objectives that go beyond the class of monotone submodular functions has been elusive. Prior to our work, the only O(1)-approximation mechanism known for non-monotone submodular objectives required an exponential number of value queries. At the heart of our approach lies a novel greedy algorithm for non-monotone submodular maximization under a knapsack constraint. Our algorithm builds two candidate solutions simultaneously (to achieve a good approximation), yet ensures that agents cannot jump from one solution to the other (to implicitly enforce truthfulness). Ours is the first mechanism for the problem where-crucially-the agents are not ordered according to their marginal value per cost. This allows us to appropriately adapt these ideas to the online setting as well. To further illustrate the applicability of our approach, we also consider the case where additional feasibility constraints are present, e.g., at most k agents can be selected. We obtain O(p)-approximation mechanisms for both monotone and non-monotone submodular objectives, when the feasible solutions are independent sets of a p-system. With the exception of additive valuation functions, no mechanisms were known for this setting prior to our work. Finally, we provide lower bounds suggesting that, when one cares about non-trivial approximation guaran

A sustainable “green” destination in the making, traversed by a cultural route

Slovenia, with around two million inhabitants and an area of just over 20,000 km2, is a relatively small country that is mainly mountainous or hilly, with a portion of plain in the east, towards the border with Hungary. It has had over a thousand years of dramatic and turbulent history. Despite repeated destruction, as well as recent extended land use, it has maintained numerous pre-existing historic territorial configurations and large areas of countryside, to the extent that it is often referred to and marketed as “Green Slovenia”. Overall, it is a very varied nation, and, at the same time, it is rich in resources and tourist attractions of different kinds. Slovenia – which is almost rectangular in shape, with a protuberance in the northeast in the Drava and Mura Statistical Regions – constitutes, within Europe, an important crossroads for transit towards: – the East, with Hungary and the rest of Eastern Europe; – the South, with Croatia and the Balkans; – the North, with Austria and Central Europe; – the West, with Italy. This position is confirmed by foreign tourism, which has developed greatly since the Second World War. Practically all of Slovenia is on dry land. Of its 212 municipalities, only Ankaran, Izola, Koper and Piran are on the (Adriatic) coast. These will be the subject of this dissertation. Having been amply involved in seaside tourism since World War II, they have now also opened up to cultural tourism. Tourism has recently also affected their immediate rural hinterland, in ways that are becoming ever more diverse. The various stakeholders – also in view of the considerable urbanisation that has involved all of the coastal belt – are dealing with the problem of sustainability, partly by adhering to the conceptions of destination governance and destination management (DM). Moreover, they are aware of the need to involve the local area in the light of the concept/instrument of a Heritage Trail. The European QNeST (Quality Network on Sustainable Tourism, https://application.qnest.eu/) project is an example and application thereof

Innovations and Social Media Analytics in a Digital Society

info:eu-repo/semantics/publishedVersio

Innovations and Social Media Analytics in a Digital Society

Recent advances in digitization are transforming healthcare, education, tourism, information technology, and some other sectors. Social media analytics are tools that can be used to measure innovation and the relation of the companies with the citizens. This book comprises state-ofthe-art social media analytics, and advanced innovation policies in the digitization of society. The number of applications that can be used to create and analyze social media analytics generates large amounts of data called big data, including measures of the use of the technologies to develop or to use new services to improve the quality of life of the citizens. Digitization has applications in fields from remote monitoring to smart sensors and other devices. Integration generates data that need to be analyzed and visualized in an easy and clear way, that will be some of the proposals of the researchers present in this book. This volume offers valuable insights to researchers on how to design innovative digital analytics systems and how to improve information delivery remotely.info:eu-repo/semantics/publishedVersio

Budget-Smoothed Analysis for Submodular Maximization

The greedy algorithm for monotone submodular function maximization subject to cardinality constraint is guaranteed to approximate the optimal solution to within a 1-1/e factor. Although it is well known that this guarantee is essentially tight in the worst case - for greedy and in fact any efficient algorithm, experiments show that greedy performs better in practice. We observe that for many applications in practice, the empirical distribution of the budgets (i.e., cardinality constraints) is supported on a wide range, and moreover, all the existing hardness results in theory break under a large perturbation of the budget. To understand the effect of the budget from both algorithmic and hardness perspectives, we introduce a new notion of budget-smoothed analysis. We prove that greedy is optimal for every budget distribution, and we give a characterization for the worst-case submodular functions. Based on these results, we show that on the algorithmic side, under realistic budget distributions, greedy and related algorithms enjoy provably better approximation guarantees, that hold even for worst-case functions, and on the hardness side, there exist hard functions that are fairly robust to all the budget distributions

ASA 2021 Statistics and Information Systems for Policy Evaluation

This book includes 40 peer-reviewed short papers submitted to the Scientific Conference titled Statistics and Information Systems for Policy Evaluation, aimed at promoting new statistical methods and applications for the evaluation of policies and organized by the Association for Applied Statistics (ASA) and the Dept. of Statistics, Computer Science, Applications DiSIA “G. Parenti” of the University of Florence, jointly with the partners AICQ (Italian Association for Quality Culture), AICQ-CN (Italian Association for Quality Culture North and Centre of Italy), AISS (Italian Academy for Six Sigma), ASSIRM (Italian Association for Marketing, Social and Opinion Research), Comune di Firenze, the SIS – Italian Statistical Society, Regione Toscana and Valmon – Evaluation & Monitoring