State-of-the-Art Report on Systems Analysis Methods for Resolution of Conflicts in Water Resources Management

Water is an important factor in conflicts among stakeholders at the local, regional, and even international level. Water conflicts have taken many forms, but they almost always arise from the fact that the freshwater resources of the world are not partitioned to match the political borders, nor are they evenly distributed in space and time. Two or more countries share the watersheds of 261 major rivers and nearly half of the land area of the wo rld is in international river basins. Water has been used as a military and political goal. Water has been a weapon of war. Water systems have been targets during the war. A role of systems approach has been investigated in this report as an approach for resolution of conflicts over water. A review of systems approach provides some basic knowledge of tools and techniques as they apply to water management and conflict resolution. Report provides a classification and description of water conflicts by addressing issues of scale, integrated water management and the role of stakeholders. Four large-scale examples are selected to illustrate the application of systems approach to water conflicts: (a) hydropower development in Canada; (b) multipurpose use of Danube river in Europe; (c) international water conflict between USA and Canada; and (d) Aral See in Asia. Water conflict resolution process involves various sources of uncertainty. One section of the report provides some examples of systems tools that can be used to address objective and subjective uncertainties with special emphasis on the utility of the fuzzy set theory. Systems analysis is known to be driven by the development of computer technology. Last section of the report provides one view of the future and systems tools that will be used for water resources management. Role of the virtual databases, computer and communication networks is investigated in the context of water conflicts and their resolution.https://ir.lib.uwo.ca/wrrr/1005/thumbnail.jp

Modified bargaining protocols for automated negotiation in open multi-agent systems

Current research in multi-agent systems (MAS) has advanced to the development of open MAS, which are characterized by the heterogeneity of agents, free exit/entry and decentralized control. Conflicts of interest among agents are inevitable, and hence automated negotiation to resolve them is one of the promising solutions. This thesis studies three modifications on alternating-offer bargaining protocols for automated negotiation in open MAS. The long-term goal of this research is to design negotiation protocols which can be easily used by intelligent agents in accommodating their need in resolving their conflicts. In particular, we propose three modifications: allowing non-monotonic offers during the bargaining (non-monotonic-offers bargaining protocol), allowing strategic delay (delay-based bargaining protocol), and allowing strategic ignorance to augment argumentation when the bargaining comprises argumentation (ignorance-based argumentation-based negotiation protocol). Utility theory and decision-theoretic approaches are used in the theoretical analysis part, with an aim to prove the benefit of these three modifications in negotiation among myopic agents under uncertainty. Empirical studies by means of computer simulation are conducted in analyzing the cost and benefit of these modifications. Social agents, who use common human bargaining strategies, are the subjects of the simulation. In general, we assume that agents are bounded rational with various degrees of belief and trust toward their opponents. In particular in the study of the non-monotonic-offers bargaining protocol, we assume that our agents have diminishing surplus. We further assume that our agents have increasing surplus in the study of delay-based bargaining protocol. And in the study of ignorance-based argumentation-based negotiation protocol, we assume that agents may have different knowledge and use different ontologies and reasoning engines. Through theoretical analysis under various settings, we show the benefit of allowing these modifications in terms of agents’ expected surplus. And through simulation, we show the benefit of allowing these modifications in terms of social welfare (total surplus). Several implementation issues are then discussed, and their potential solutions in terms of some additional policies are proposed. Finally, we also suggest some future work which can potentially improve the reliability of these modifications

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

Simulation of automated negotiation

Durch die Automatisierung von Verhandlungen sollen bessere Verhandlungsergebnisse erzielt werden können als bei Verhandlungen zwischen Menschen und neue Koordinationsformen für autonome Agentensysteme ermöglicht werden. Diese Arbeit beschäftigt sich mit der Simulation solcher Systeme für automatisierte Verhandlungen, da operative Systeme zur Zeit noch nicht verfügbar sind. Die Arbeit basiert auf einer Erhebung und Diskussion der aktuellen Literatur im Bereich der Simulation automatisierter Verhandlungen. Existierende Ansätze weisen einige Unzulänglichkeiten bezüglich deren praktischer Umsetzbarkeit in einer offenen Umgebung wie dem Internet auf, wo automatisierte Verhandlungen nicht nur sehr schnell durchgeführt werden sondern sich auch Software-Agenten und Verhandlungsprobleme ändern können. Diese Defizite thematisierend werden Verhandlungssysteme für automatisierte Verhandlungen vorgeschlagen. Diese bestehen zum einen aus Software-Agenten, die generische Angebots- und Konzessionsstratgien verfolgen, zum anderen aus Interaktionsprotokollen, die es Agenten erlauben ihre Strategien vorübergehend oder permanent auszusetzen. Ergebnisse der Simulation dieser Systeme, mit Verhandlungsproblemen aus Verhandlungsexperimenten mit menschlichen Probanden als Input, werden für unterschiedliche Ergebnisdimensionen -- Übereinkunftshäufigkeit, Fairness, individuelle und kollektive Effizienz -- zwischen Systemen und auch mit den Ergebnissen der Experimente verglichen. Trotz fundamentaler Zielkonflikte zwischen den einzelnen Ergebnisdimensionen erzielen einige Systeme konsistent bessere Ergebnisse sowohl im Systemvergleich als auch verglichen mit den Ergebnissen der Experimente. Diese Systeme bestehen aus Software-Agenten die systematisch Angebote mit monoton abnehmendem Nutzen unterbreiten und erste Konzessionensschritte tätigen solange der Opponent bisherige Konzessionen erwidert hat. Das verwendete Interaktionsprotokoll zeichnet sich dadurch aus, dass es den Agenten erlaubt ungünstige Angebote zurückzuweisen und damit neue Angebote des Opponenten einzufordern, durch diese Unterbrechung der eigenen Angebotsstrategie können ungünstige Verhandlungsergebnisse vermieden werden.Automated negotiation is argued to improve negotiation outcomes by replacing humans and to enable coordination in autonomous systems. As operative systems do not yet exist scholars rely on simulations to evaluate potential systems for automated negotiation. This dissertation reviews the state of the art literature on simulation of automated negotiation along its main components - negotiation problem, interaction protocol, and software agents. Deficiencies of existing approaches concerning the practical application in an open environment as the Internet - where automated negotiation proceeds fast, with changing opponents, and for various negotiation problems - are identified. To address these deficiencies we develop and simulate automated negotiation systems, consisting of software agents that follow generic offer generation and concession strategies and protocols that allow these agents to interrupt their strategy to avoid exploitation and unfavorable agreements. Outcomes of simulation runs are compared across systems and to human negotiation along various outcome dimensions - proportion of agreements, dyadic and individual performance, and fairness - for various negotiation problems derived from negotiation experiments with human subjects. Though there exist trade-offs between the different outcome dimensions, systems consisting of software agents, that systematically propose offers of monotonically decreasing utility and make first concession steps if the opponent reciprocated previous concessions, and an interaction protocol that enables to reject unfavorable offers - without immediately aborting negotiations - in order to elicit new offers from the opponent, performed best. These systems performed very well in all outcome dimensions when compared with other systems and were the only that outperformed negotiation between humans in all dimensions

Multi-energy retail market simulation with autonomous intelligent agents

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2005. Faculdade de Engenharia. Universidade do Port

Final Bid Price Estimation for Negotiated Contracts: Bargaining Game Theory Approach

The wide use of the low bid method by employers for awarding construction contracts has created an aggressively competitive environment among contractors in the construction industry. As a result, a contractor may resort to use a low mark-up percentage for his bid to increase his chances of winning, which may lead to losses and conflicts in case he is awarded the project. Additionally, a contractor who reaches the final negotiations stage for a certain project is faced by the dilemma of the minimum discount percentage he may need to offer to the employer that maximizes his chance to win the project. This research presents the framework for a decision support tool / model that uses bargaining game theory to help contractors make rational decisions regarding the discount percentage to offer to the employer during negotiations in order to establish a win-win scenario in which the employer gets the lowest possible price for his project and at the same time the contractor’s profit is maximized. The developed Monte Carlo simulation based python model uses the source code of Gambit in order to determine the Nash Equilibrium of a typical negotiation process in private sector projects; where negotiations are allowed, contractors are procured through competitive bidding, and the low bid method is used for awarding the contracts. The negotiation process is depicted by a game composed of three players (two contractors and one employer), through a two stage negotiation process. Moreover, a real case study of a hospital mega project in Egypt is used to validate the developed python model. The analysis of this case study showed that using the developed model by the winning contractor could have saved him almost 299.5 M EGP of unnecessary discount offered to the employer. Additionally, another objective of this research is to determine and rank the factors that affect the level of aggression (bargaining power) of the two negotiating parties (employer/contractor) in the Egyptian market

A Reinforcement Learning Quality of Service Negotiation Framework For IoT Middleware

The Internet of Things (IoT) ecosystem is characterised by heterogeneous devices dynamically interacting with each other to perform a specific task, often without human intervention. This interaction typically occurs in a service-oriented manner and is facilitated by an IoT middleware. The service provision paradigm enables the functionalities of IoT devices to be provided as IoT services to perform actuation tasks in critical-safety systems such as autonomous, connected vehicle system and industrial control systems. As IoT systems are increasingly deployed into an environment characterised by continuous changes and uncertainties, there have been growing concerns on how to resolve the Quality of Service (QoS) contentions between heterogeneous devices with conflicting preferences to guarantee the execution of mission-critical actuation tasks. With IoT devices with different QoS constraints as IoT service providers spontaneously interacts with IoT service consumers with varied QoS requirements, it becomes essential to find the best way to establish and manage the QoS agreement in the middleware as a compromise in the QoS could lead to negative consequences. This thesis presents a QoS negotiation framework, IoTQoSystem, for IoT service-oriented middleware. The QoS framework is underpinned by a negotiation process that is modelled as a Markov Decision Process (MDP). A model-based Reinforcement Learning negotiation strategy is proposed for generating an acceptable QoS solution in a dynamic, multilateral and multi-parameter scenarios. A microservice-oriented negotiation architecture is developed that combines negotiation, monitoring and forecasting to provide a self-managing mechanism for ensuring the successful execution of actuation tasks in an IoT environment. Using a case study, the developed QoS negotiation framework was evaluated using real-world data sets with different negotiation scenarios to illustrate its scalability, reliability and performance