A Comparison of Bidding Strategies for Online Auctions Using Fuzzy Reasoning and Negotiation Decision Functions

© 1993-2012 IEEE. Bidders often feel challenged when looking for the best bidding strategies to excel in the competitive environment of multiple and simultaneous online auctions for same or similar items. Bidders face complicated issues for deciding which auction to participate in, whether to bid early or late, and how much to bid. In this paper, we present the design of bidding strategies, which aim to forecast the bid amounts for buyers at a particular moment in time based on their bidding behavior and their valuation of an auctioned item. The agent develops a comprehensive methodology for final price estimation, which designs bidding strategies to address buyers' different bidding behaviors using two approaches: Mamdani method with regression analysis and negotiation decision functions. The experimental results show that the agents who follow fuzzy reasoning with a regression approach outperform other existing agents in most settings in terms of their success rate and expected utility

Negotiation-Based Capacity Planning With A Learning Mechanism Using Adaptive Neurofuzzy Inference System

In decentralized manufacturing environment with multiple factories that are scattered geographically, the complexity of production systems increases, and capacity planning and allocation of resources have become a significant concern that affects system performances. This study focuses on the development of an integrated framework to allocate limited budget in a multiple-factory environment. We develop a negotiation framework with learning mechanism to allocate autonomously finite budget provided by a headquarter and to facilitate the use of limited manufacturing resources that are scattered over individual factories. The outcome of the experiments shows good prediction of the opponent offers during negotiation, so it enables the reduction of negotiation time

Human-Computer Negotiations: A Systematic Evaluation of the Effects of Timespan, Tactic, and Search Mechanism

Artificial Intelligence and Computer Agents are having a substantial impact on our everyday lives. The current paper focuses on the prospects of humans negotiating with computer agents in e-commerce settings. We conducted experiments where the subjects negotiated the purchase of mobile plans with computer agents acting as sellers. Three time-based negotiation tactics and two search mechanisms were employed in synchronous vs. asynchronous sessions. The results suggest that computer agents’ negotiation tactics and search mechanisms have significant effects on both the subjective and objective outcomes of the negotiations, while timespan has marginal effects on the agreement rate of the negotiation

Can a Negotiator Build a Tough Impression Without Chatting? —— Implicit Power and its Influence on Human-Computer Negotiation

In this paper, we studied the influence of implicit power in an e-commerce setting where humans negotiated with computer agents. Implicit power is defined as a kind of perceived power gained indirectly through offer exchange. In much of the past research, power was always considered to be expressed directly through chat or natural language communications during negotiation. We suggest that there is another mode of expressing power other than chat: implicitly influencing. Specifically, we designed an experiment where several aspects of implicit power were studied: anchoring, agent profile image, and experiment subjects’ personality. In our experiment, the subjects negotiated the purchase of a laptop with computer agents acting as sellers. The result suggested that implicit power indeed influenced the negotiation result

Efficient Communication in Agent-based Autonomous Logistic Processes

Transportation of goods plays a vital role for the success of a logistics network. The ability to transport goods quickly and cost effectively is one of the major requirements of the customers. Dynamics involved in the logistics process like change or cancellation of orders or uncertain information about the orders add to the complexity of the logistic network and can even reduce the efficiency of the entire logistics process. This brings about a need of integrating technology and making the system more autonomous to handle these dynamics and to reduce the complexity. Therefore, the distributed logistics routing protocol (DLRP) was developed at the University of Bremen. In this thesis, DLRP is extended with the concept of clustering of transport goods, two novel routing decision schemes and a negotiation process between the cluster of goods and the vehicle. DLRP provides the individual logistic entities the ability to perform routing tasks autonomously e.g., discovering the best route to the destination at the given time. Even though DLRP seems to solve the routing problem in real-time, the amount of message flooding involved in the route discovery process is enormous. This motivated the author to introduce a cluster-based routing approach using software agents. The DLRP along with the clustering algorithm is termed as the cluster-based DLRP. In the latter, the goods are first clustered into groups based on criteria such as the common destination. The routing is now handled by the cluster head rather than the individual transport goods which results in a reduced communication volume in the route discovery. The latter is proven by evaluating the performance of the cluster-based DLRP approach compared to the legacy DLRP. After the routing process is completed by the cluster heads, the next step is to improve the transport performance in the logistics network by identifying the best means to transport the clustered goods. For example, to have better utilization of the transport capacity, clusters can be transported together on a stretch of overlapping route. In order to make optimal transport decisions, the vehicle calculates the correlation metric of the routes selected by the various clusters. The correlation metric aids in identifying the clusters which can be transported together and thereby can result in better utilization of the transport resources. In turn, the transportation cost that has to be paid to the vehicle can be shared between the different clusters. The transportation cost for a stretch of route is calculated by the vehicle and offered to the cluster. The latter can decide based upon the transportation cost or the selected route whether to accept the transport offer from the vehicle or not. In this regard, different strategies are developed and investigated. Thereby a performance evaluation of the capacity utilization of the vehicle and the transportation cost incurred by the cluster is presented. Finally, the thesis introduces the concept of negotiation in the cluster based routing methods. The negotiation process enhances the transport decisions by giving the clusters and the vehicles the flexibility to negotiate the transportation cost. Thus, the focus of this part of the thesis is to analyse the negotiation strategies used by the logistics entities and their role in saving negotiation time while achieving a favorable transportation cost. In this regard, a performance evaluation of the different proposed strategies is presented, which in turn gives the logistics practitioners an overview of the best strategy to be deployed in various scenarios. Clustering of goods aid in the negotiation process as on the one hand, a group of transport goods have a stronger basis for negotiation to achieve a favorable transportation price from the vehicle. On the other hand it makes it easier for the vehicle to select the packages for transport and helps the vehicle to operate close to its capacity. In addition, clustering enables the negotiation process to be less complex and voluminous. From the analytical considerations and obtained results in the three parts of this thesis, it can be concluded that efficient transport decisions, though very complex in a logistics network, can be simplified to a certain extent utilizing the available information of the goods and vehicles in the network

Evaluations of Tactics for Automated Negotiations

[[abstract]]Automated negotiation under the infrastructure of e-commerce is becoming an important issue. However, although the communication protocols and frameworks of automated negotiation have been extensively investigated, the corresponding tactics and strategies are still underdeveloped and need to be evaluated further. Based on the negotiation model proposed by Faratin et al., this paper examines the performance of automated negotiation tactics and intends to provide concise suggestions for the users of automated negotiation. First, theoretical analysis is used to evaluate the behavior-dependent tactics. Constructive conclusions are obtained when single-issue negotiations are considered. Next, a new framework for applying single-issue tactics to multi-issue negotiation is proposed. Based on this framework, theoretical analysis is then extended to multi-issue cases. Finally, different from the previous work, exhaustive simulations based on two-issue negotiations are performed to evaluate the effectiveness of behavior-dependent and time-dependent tactics. The experimental results provide several important insights into negotiation tactics.[[booktype]]紙本[[booktype]]電子

Managing application software suppliers in information system development projects

Information system development (ISD) projects have been associated with the "software crisis" for over three decades. A set of common "root causes" has often been cited in literature with corresponding "solutions". Yet the overall project success rate has remained low, resulting in a paradox of many solutions and little progress over the years. This study examines the management of application software acquisition from external suppliers in ISD projects. Three case studies are documented based on participant observation with complete membership roles. After within-case analyses highlighting issues in individual cases, crosscase analyses are conducted, first to identify a pattern of ISD project challenges and then to search for their explanations. Concepts from agency theory, contract theory and product development literature are used in the process of diagnosing root causes behind the observations. The proposed explanation is that the Traditional Systems Development Framework (TSDF), characterized by competitive-bidding-monopolized-development, underlies the identified root causes. Accordingly, competitive development is suggested as an alternative approach. Following the "Inference to the Best Explanation" (IBE) analytical strategy, the suggested approach is subject to two contrastive analyses, first with the prepackaged software development and then with the construction industry, to demonstrate that the suggestion is a "warranted inference". Further analogical analyses illustrate the feasibility of development competition for software product development. A Performance-Based Systems Development Framework (PBSDF) is outlined as a tentative implementation of the suggested competitive development approach for ISD projects supported by risk-sharing supplier contract and a relative product evaluation approach. A number of future research implications are described as a result of this study after summarizing the research contributions

Agent-Based Simulation of Financial Markets: A Modular, Continuous-time Approach

The dynamics of financial markets is subject of much debate among researchers and financial experts trying to understand and explain how financial markets work and traders behave. Diversified explanations result from the complexity of markets, and the hardly observable aspects of price formation mechanisms and of participants' motivation behind trading decisions. In an attempt to provide a better understanding of market dynamics, studies in the realm of agent-based computational economics represent markets from bottom-up. The aim of this thesis is to contribute to the understanding of market dynamics by extending the agent-based computational approach. In order to achieve our goal we propose a modular, continuous-time, agent-based trading environment, with individual, autonomous representation of market participants. In order to be able to develop such an environment we first analyze and compare real and artificial stock markets (ASMs). Based on this analysis we propose a conceptual framework to describe real markets. By enriching the framework with design and implementation issues we get a multi-dimensional taxonomy of artificial stock markets. ABSTRACTE, the proposed modular environment is an operational form of these frameworks. ABSTRACTE is aimed to embed the common aspects of real markets that exhibit big variations and are rarely represented in artificial stock markets. This environment provides the user with a flexible mechanism to implement many of the varying and hardly observable aspects of stock markets and traders' behavior. In this way it can contribute to the understanding of market dynamics as it can be used both as a test bed to replicate and evaluate existing market models, and to compare dynamics of multiple ASMs, as well as a tool to conduct experiments with new models and traders

Partnerships on Colorado conservation lands: social-ecological outcomes of collaborative grazing management

Includes bibliographical references.2022 Fall.To view the abstract, please see the full text of the document

Closing Information Gaps with Need-driven Knowledge Sharing

Informationslücken schließen durch bedarfsgetriebenen Wissensaustausch Systeme zum asynchronen Wissensaustausch – wie Intranets, Wikis oder Dateiserver – leiden häufig unter mangelnden Nutzerbeiträgen. Ein Hauptgrund dafür ist, dass Informationsanbieter von Informationsuchenden entkoppelt, und deshalb nur wenig über deren Informationsbedarf gewahr sind. Zentrale Fragen des Wissensmanagements sind daher, welches Wissen besonders wertvoll ist und mit welchen Mitteln Wissensträger dazu motiviert werden können, es zu teilen. Diese Arbeit entwirft dazu den Ansatz des bedarfsgetriebenen Wissensaustauschs (NKS), der aus drei Elementen besteht. Zunächst werden dabei Indikatoren für den Informationsbedarf erhoben – insbesondere Suchanfragen – über deren Aggregation eine fortlaufende Prognose des organisationalen Informationsbedarfs (OIN) abgeleitet wird. Durch den Abgleich mit vorhandenen Informationen in persönlichen und geteilten Informationsräumen werden daraus organisationale Informationslücken (OIG) ermittelt, die auf fehlende Informationen hindeuten. Diese Lücken werden mit Hilfe so genannter Mediationsdienste und Mediationsräume transparent gemacht. Diese helfen Aufmerksamkeit für organisationale Informationsbedürfnisse zu schaffen und den Wissensaustausch zu steuern. Die konkrete Umsetzung von NKS wird durch drei unterschiedliche Anwendungen illustriert, die allesamt auf bewährten Wissensmanagementsystemen aufbauen. Bei der Inversen Suche handelt es sich um ein Werkzeug das Wissensträgern vorschlägt Dokumente aus ihrem persönlichen Informationsraum zu teilen, um damit organisationale Informationslücken zu schließen. Woogle erweitert herkömmliche Wiki-Systeme um Steuerungsinstrumente zur Erkennung und Priorisierung fehlender Informationen, so dass die Weiterentwicklung der Wiki-Inhalte nachfrageorientiert gestaltet werden kann. Auf ähnliche Weise steuert Semantic Need, eine Erweiterung für Semantic MediaWiki, die Erfassung von strukturierten, semantischen Daten basierend auf Informationsbedarf der in Form strukturierter Anfragen vorliegt. Die Umsetzung und Evaluation der drei Werkzeuge zeigt, dass bedarfsgetriebener Wissensaustausch technisch realisierbar ist und eine wichtige Ergänzung für das Wissensmanagement sein kann. Darüber hinaus bietet das Konzept der Mediationsdienste und Mediationsräume einen Rahmen für die Analyse und Gestaltung von Werkzeugen gemäß der NKS-Prinzipien. Schließlich liefert der hier vorstellte Ansatz auch Impulse für die Weiterentwicklung von Internetdiensten und -Infrastrukturen wie der Wikipedia oder dem Semantic Web