Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

Digital Revolution, Financial Infrastructure and Entrepreneurship: The Case of India

Digital Revolution has been sweeping across the world over the last three decades. This revolution has spread far more rapidly, especially in developing countries, than was the case with either the Industrial or Agricultural Revolution. Indeed, the spread has been so rapid that China has become its major driver with India emerging as one as well. This paper is devoted to two aspects of the Digital Revolution as it impacts India: financial technology or fintech, and innovation and entrepreneurship. As in other countries, the spread of digital technologies has led to a dramatic transformation of financial infrastructure in India. On the one hand, this has improved efficiency and on the other it has led to increased financial inclusion. The government’s payments system has evolved to a point that it can make payments directly to individuals and firms through bank accounts. Individuals are seamlessly able to transfer funds from their bank accounts to those of others. Businesses and customers can transact digitally in real time. Digital technologies have also helped democratize innovation and entrepreneurship. Unlike conventional technologies, digital innovations are less costly to commercialize on average. Scaling up of conventional innovations requires a large volume of investment. In contrast, many digital innovations lend themselves to scaling up at low costs. As a result, in the digital space, innovators themselves are often seen as turning into entrepreneurs. The sharp division between innovators and entrepreneurs that existed in the past has greatly diminished. I divide the paper into three parts. Part 1 focuses on the spread of financial technologies in India. Part 2 considers how the digital revolution has helped spawn and transform the nature of entrepreneurship in the country. Part 3 offers some concluding remarks

Optimization Methods for Mobility Resource Allocation, Pricing and Demand Management in Mobility-as-a-Service Systems

In the Mobility-as-a-Service (MaaS) systems under government contracting, this thesis proposes innovative auction-based MaaS mechanisms where users arrive dynamically and compete for mobility resources by bidding for mode-agnostic mobility resources based on their willingness to pay and preferences on service experience. This thesis takes the perspective of a MaaS regulator, which aims to maximize social welfare by allocating mobility resources to users. This thesis proposes two MaaS mechanisms that allow users to either pay for the immediate use of mobility service, Pay-as-You-Go (PAYG), or subscribe to mobility service packages, Pay-as-a-Package (PAAP). This thesis casts the proposed mechanisms as online mobility resource allocation problems to accommodate user bids based on available mobility resources. It is shown that the proposed PAYG mechanism is incentive-compatible, individually rational, and budget-balanced. This thesis proposes two polynomial-time online algorithms for both mechanisms and derives its corresponding competitive ratio relative to an offline optimization problem. The thesis also explores rolling horizon configurations with varying look-ahead policies to implement the proposed mechanisms. In the MaaS systems under economic deregulation, a MaaS platform can be viewed as a two-sided market where travelers and transportation service providers (TSPs) are two groups of interacting agents. This thesis proposes an optimization framework for the regulation of two-sided MaaS markets, uses an auction mechanism to model the behavior of travelers and TSPs, and casts this problem as a single-leader multi-follower game (SLMFG) where the leader is the MaaS regulator and two groups of follower problems represent the travelers and the TSPs. The MaaS regulator aims to maximize its profits by optimizing service prices and resource allocation. In response, travelers (resp. TSPs) adjust their participation level in the MaaS platform to minimize their travel costs (resp. maximize their profits). This thesis analyzes network effects in the two-sided MaaS market and formulates SLMFGs without/with network effects. This thesis provides constraint qualifications for the proposed SLMFGs and develops customized branch-and-bound algorithms based on strong-duality reformulations to solve SLMFGs. Considering the MaaS ecosystems with multi-disciplinary collaborators, this thesis models a MaaS ecosystem providing mobility services and instant delivery services by sharing the same transport system. This thesis derives integrated mobility and delivery user equilibrium (IMDUE) in the MaaS ecosystem and proposes a bilateral surcharge and reward scheme (BSRS) to manage the integrated mobility and delivery demand in different scenarios. This thesis proposes a bilevel model to optimize the proposed BSRS, where the upper-level problem aims to minimize the total system equilibrium costs of mobility and delivery users and the lower-level problem is the derived IMDUE under BSRS. After exploring the properties of the BSRS, a trial-and-error solution algorithm is proposed to solve the proposed bilevel optimization problem based on the properties of the optimal solutions under BSRS. Overall, this thesis proposes a unified framework and tractable optimization methodologies for the innovative MaaS paradigm, exploits the potentialities of MaaS systems to evaluate futuristic transport scenarios, and provides meaningful managerial insights for the regulation of MaaS systems

Study to gather evidence on the working conditions of platform workers VT/2018/032 Final Report 13 December 2019

Platform work is a type of work using an online platform to intermediate between platform workers, who provide services, and paying clients. Platform work seems to be growing in size and importance. This study explores platform work in the EU28, Norway and Iceland, with a focus on the challenges it presents to working conditions and social protection, and how countries have responded through top-down (e.g. legislation and case law) and bottom-up actions (e.g. collective agreements, actions by platform workers or platforms). This national mapping is accompanied by a comparative assessment of selected EU legal instruments, mostly in the social area. Each instrument is assessed for personal and material scope to determine how it might impact such challenges. Four broad legal domains with relevance to platform work challenges are examined in stand-alone reflection papers. Together, the national mapping and legal analysis support a gap analysis, which aims to indicate where further action on platform work would be useful, and what form such action might take

Shared Mobility - Operations and Economics

In the last decade, ubiquity of the internet and proliferation of smart personal devices have given rise to businesses that are built on the foundation of the sharing economy. The mobility market has implemented the sharing economy model in many forms, including but not limited to, carsharing, ride-sourcing, carpooling, taxi-sharing, ridesharing, bikesharing, and scooter sharing. Among these shared-use mobility services, ridesharing services, such as peer-to-peer (P2P) ridesharing and ride-pooling systems, are based on sharing both the vehicle and the ride between users, offering several individual and societal benefits. Despite these benefits, there are a number of operational and economic challenges that hinder the adoption of various forms of ridesharing services in practice. This dissertation attempts to address these challenges by investigating these systems from two different, but related, perspectives. The successful operation of ridesharing services in practice requires solving large-scale ride-matching problems in short periods of time. However, the high computational complexity and inherent supply and demand uncertainty present in these problems immensely undermines their real-time application. In the first part of this dissertation, we develop techniques that provide high-quality, although not necessarily optimal, system-level solutions that can be applied in real time. More precisely, we propose a distributed optimization technique based on graph partitioning to facilitate the implementation of dynamic P2P ridesharing systems in densely populated metropolitan areas. Additionally, we combine the proposed partitioning algorithm with a new local search algorithm to design a proactive framework that exploits historical demand data to optimize dynamic dispatching of a fleet of vehicles that serve on-demand ride requests. The main purpose of these methods is to maximize the social welfare of the corresponding ridesharing services. Despite the necessity of developing real-time algorithmic tools for operation of ridesharing services, solely maximizing the system-level social welfare cannot result in increasing the penetration of shared mobility services. This fact motivated the second stream of research in this dissertation, which revolves around proposing models that take economic aspects of ridesharing systems into account. To this end, the second part of this dissertation studies the impact of subsidy allocation on achieving and maintaining a critical mass of users in P2P ridesharing systems under different assumptions. First, we consider a community-based ridesharing system with ride-back guarantee, and propose a traveler incentive program that allocates subsidies to a carefully selected set of commuters to change their travel behavior, and thereby, increase the likelihood of finding more compatible and profitable matches. We further introduce an approximate algorithm to solve large-scale instances of this problem efficiently. In a subsequent study for a cooperative ridesharing market with role flexibility, we show that there may be no stable outcome (a collusion-free pricing and allocation scheme). Hence, we introduced a mathematical formulation that yields a stable outcome by allocating the minimum amount of external subsidy. Finally, we propose a truthful subsidy scheme to determine matching, scheduling, and subsidy allocation in a P2P ridesharing market with incomplete information and a budget constraint on payment deficit. The proposed mechanism is shown to guarantee important economic properties such as dominant-strategy incentive compatibility, individual rationality, budget-balance, and computational efficiency. Although the majority of the work in this dissertation focuses on ridesharing services, the presented methodologies can be easily generalized to tackle related issues in other types of shared-use mobility services.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169843/1/atafresh_1.pd