INVESTIGATING AGENT AND TASK OPENNESS IN ADHOC TEAM FORMATION

When deciding which ad hoc team to join, agents are often required to consider rewards from accomplishing tasks as well as potential benefits from learning when working with others, when solving tasks. We argue that, in order to decide when to learn or when to solve task, agents have to consider the existing agents’ capabilities and tasks available in the environment, and thus agents have to consider agent and task openness—the rate of new, previously unknown agents (and tasks) that are introduced into the environment. We further assume that agents evolve their capabilities intrinsically through learning by observation or learning by doing when working in a team. Thus, an agent will need to consider which task to do or which team to join would provide the best situation for such learning to occur. In this thesis, we develop an auction-based multiagent simulation framework, a mechanism to simulate openness in our environment, and conduct comprehensive experiments to investigate the impact of agent and task openness. We propose several agent task selection strategies to leverage the environmental openness. Furthermore, we present a multiagent solution for agent-based collaborative human task assignment when finding suitable tasks for users in complex environments is made especially challenging by agent openness and task openness. Using an auction-based protocol to fairly assign tasks, software agents model uncertainty in the outcomes of bids caused by openness, then acquire tasks for people that maximize both the user’s utility gain and learning opportunities for human users (who improve their abilities to accomplish future tasks through learning by experience and by observing more capable humans). Experimental results demonstrate the effects of agent and task openness on collaborative task assignment, the benefits of reasoning about openness, and the value of non-myopically choosing tasks to help people improve their abilities for uncertain future tasks

The process improvement dilemma in dynamic 3PL firms: A systems and agency lens

For the past several decades, firms have been shifting from contending as autonomous entities to working and competing as part of supply chains. In this context, warehousing, transportation, and distribution needs are being increasingly outsourced to third-party logistics (3PL) firms. 3PL providers operate in fast-moving, time-sensitive, and priority-changing supply chain environments, constantly demanding efficient, cost-effective, and routinized responses. To attain the ultimate end of maximizing efficiency, reducing costs, and improving customer satisfaction, scholars and supply chain industry opinion leaders alike talk about process improvement as part of a broader organizational learning strategy to be pursued in order to keep a competitive edge. This thesis explores the relationship between daily bottom-line pressures and prioritization and the design, implementation, and control of process improvement initiatives in complex and dynamic 3PL service providers. It uses a systems-agency lens to unveil intra- and inter-firm relations around process improvement activity and the links with organizational learning. The study utilized multi-case study-based qualitative-interpretive methods used in conjunction with system dynamics and agency tools. Data collection was carried out through in-depth interviews with 41 employees from two 3PL service providers and complemented by two collaborative enquiry exercises organized for each case study firm. Contrary to recommendations made by scholars and industry leaders, this thesis has found that day-to-day operational firefighting in 3PL scenarios revolving around managing multiple demands, conflicting priorities, and unexpected events often prevail over less tangible process improvement and broader organizational learning goals. This is aggravated by constant cost-reduction pressures centering on human resources headcount deemed critical for the development of learning and improvement practices. Consequently, there is little evidence that the case study firms demonstrate the necessary conditions for process improvement and organizational learning to actually take place. The study also revealed that when process improvement does happen, its focus mainly centers on customer satisfaction or cost-saving, rather than on the improvement of shop floor work routines aiming at operational effectiveness. It also shows process improvement to be more reactive and ad hoc as opposed to the continuous, widespread, and long-term-oriented practices associated with continuous improvement and organizational learning

Managing Supplier Involvement in New Product Development: A Multiple-Case Study

Existing studies of supplier involvement in new product development have mainly focused on project-related short-term processes and success-factors. This study validates and extends an existing exploratory framework, which comprises both long-term strategic processes and short-term operational processes that are related to supplier involvement. The empirical validation is based on a multiple-case study of supplier collaborations at a manufacturer in the copier and printer industry. The analysis of eight cases of supplier involvement reveals that the results of supplier-manufacturer collaborations and the associated issues and problems can best be explained by the patterns in the extent to which the manufacturer manages supplier involvement in the short-term ànd the long-term. We find that our initial framework is helpful in understanding why certain collaborations are not effectively managed, yet conclude that the existing analytical distinction between four different management areas does not sufficiently reflect empirical reality. This leads us to reconceptualize and further detail the framework. Instead of four managerial areas, we propose to distinguish between the Strategic Management arena and the Operational Management arena. The Strategic Management arena contains processes that together provide long-term, strategic direction and operational support for project teams adopting supplier involvement. These processes also contribute to building up a supplier base that can meet current and future technology and capability needs. The Operational Management arena contains processes that are aimed at planning, managing and evaluating the actual collaborations in a specific development project. The results of this study suggest that success of involving suppliers in product development is reflected by the firm’s ability to capture both short-term and long-term benefits. If companies spend most of their time on operational management in development projects, they will fail to use the ‘leverage’ effect of planning and preparing such involvement through strategic management activities. Also, they will not be sufficiently able to capture possible long-term technology and learning benefits that may spin off from individual projects. Long-term collaboration benefits can only be captured if a company can build long-term relationships with key suppliers, where it builds learning routines and ensures that the capability sets of both parties are aligned and remain useful for future joint projects.Purchasing;Innovation;New Product Development;R&D Management;Supplier Relations

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Collaborative environment to support a professional community

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de ComputadoresRecent manufacturing roadmaps stress current production systems limitations, emphasizing social, economic and ecologic consequences for Europe of a non-evolution to sustainable Production Systems. Hence, both academic institutions and enterprises are committed to develop solutions that would endow enterprises to survive in nowadays’ extremely competitive business environment. A research effort is being carried on by the Evolvable Production Systems consortium towards attaining Production Systems that can cope with current technological, economical, ecological and social demands fulfilling recent roadmaps. Nevertheless research success depends on attaining consensus in the scientific community and therefore an accurate critical mass support is required in the whole process. The main goal of this thesis is the development of a Collaborative Environment Tool to assist Evolvable Production Systems consortium in such research efforts and to enhance Evolvable Assembly Systems paradigm dissemination. This work resulted in EASET (Evolvable Assembly Systems Environment Tool), a collaborative environment tool which promotes EAS dissemination and brings forth improvements through the raise of critical mass and collaboration between entities

Federated Embedded Systems – a review of the literature in related fields

This report is concerned with the vision of smart interconnected objects, a vision that has attracted much attention lately. In this paper, embedded, interconnected, open, and heterogeneous control systems are in focus, formally referred to as Federated Embedded Systems. To place FES into a context, a review of some related research directions is presented. This review includes such concepts as systems of systems, cyber-physical systems, ubiquitous computing, internet of things, and multi-agent systems. Interestingly, the reviewed fields seem to overlap with each other in an increasing number of ways