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

Development of automated dynamic bidding agents for final price prediction in online auctions

University of Technology, Sydney. Faculty of Engineering and Information Technology.Online auctions have emerged as a well-recognised paradigm of item exchange over the past few years. In these environments, software agents are being used increasingly and promisingly to bid on or trade goods. This thesis presents an automated dynamic bidding agent framework that makes use of machine learning techniques to forecast bid amounts in simultaneous auctions of the same or similar items. The availability of numerous auctions of similar items complicates the situation of bidders who wish to choose the auction where their participation will give maximum surplus. These bidders also face a perpetual dilemma about how to predict an item’s bargain price. Further, the diverse price dynamics of auctions for the same or similar items affect both the choice of auction and the valuation of the auctioned items. There is, thus, a critical need to characterise auctions based on their price dynamics before selecting one to compete in and assessing the true value of the auctioned items. The main contributions of this thesis are its development of: (i) an automated dynamic bidding agent framework, (ii) an initial price estimation methodology for choosing an auction and assessing the value of auctioned goods, (iii) a final price prediction methodology that designs bidding strategies for buyers with different bidding behaviours and (iv) a simulated electronic marketplace for implementing and evaluating the performance of bidding agents. The automated dynamic bidding agent (ADBA) framework selects an auction to participate in and predicts its final price in two phases: the first gives an initial estimation and the second phase delivers a final price prediction. The methodology for initial price estimation finds an auction to compete in and assesses the value of the auctioned item using data mining techniques. It handles the problem of diverse price dynamics in auctions for the same or similar items, using a clustering-based bid mapping and selection approach to locate the auction where participation would give maximum surplus. The value of the item is assessed with parametric and non-parametric machine learning approaches to predict the auction’s closing price. The proposed approach is validated using real online auction datasets. These results demonstrate that this clustering-based price prediction approach outperforms existing methodologies in terms of prediction accuracy. This thesis also introduces a methodology for final price estimation which designs bidding strategies to address buyers’ different bidding behaviours. This draws on two approaches: negotiation decision functions and fuzzy reasoning techniques. The bidding strategies are designed based on the bidder's own attitude to win the auction and the behaviour of rival bidders. A simulated electronic marketplace is implemented and developed using Java Agent DEvelopment Framework (JADE). The marketplace is also used to demonstrate the performance of the bidding strategies. The outcomes for heterogeneous and homogeneous bidders are measured separately in a wide variety of test environments subject to different auction settings and bidding restrictions. The results show that ADBA agents who follow this study’s bidding strategies outperform other existing agents in most settings in terms of their success rate and expected utility

Q-Strategy: A Bidding Strategy for Market-Based Allocation of Grid Services

The application of autonomous agents by the provisioning and usage of computational services is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic service provisioning and usage of Grid services, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a bidding agent framework for implementing artificial bidding agents, supporting consumers and providers in technical and economic preference elicitation as well as automated bid generation by the requesting and provisioning of Grid services. Secondly, we introduce a novel consumer-side bidding strategy, which enables a goal-oriented and strategic behavior by the generation and submission of consumer service requests and selection of provider offers. Thirdly, we evaluate and compare the Q-strategy, implemented within the presented framework, against the Truth-Telling bidding strategy in three mechanisms – a centralized CDA, a decentralized on-line machine scheduling and a FIFO-scheduling mechanisms

Using fuzzy set approach in multi-attribute automated auctions

This paper designs a novel fuzzy attributes and competition based bidding strategy (FAC-Bid), in which the final best bid is calculated on the basis of the assessment of multiple attributes of the goods and the competition for the goods in the market. The assessment of attributes adapts the fuzzy sets technique to handle uncertainty of the bidding process. The bidding strategy also uses and determines competition in the market (based on the two factors i.e. no. of the bidders participating and the total time elapsed for an auction) using Mamdani's Direct Method. Then the final price of the best bid will be determined based on the assessed attributes and the competition in the market using fuzzy reasoning technique

Fuzzy Logic Based Negotiation in E-Commerce

The evolution of multi-agent system (MAS) presents new challenges in computer science and software engineering. A particularly challenging problem is the design of various forms of interaction among agents. Interaction may be aimed at enabling agents to coordinate their activities, cooperate to reach common objectives, or exchange resources to better achieve their individual objectives. This thesis is dealing with negotiation in e-commerce: a process through which multiple self-interested agents can reach agreement over the exchange of scarce resources. In particular, we present a fuzzy logic-based negotiation approach to automate multi-issue bilateral negotiation in e-marketplaces. In such frameworks issues to negotiate on can be multiple, interrelated, and may not be fixed in advance. Therefore, we use fuzzy inference system to model relations among issues and to allow agents express their preferences on them. We focus on settings where agents have limited or uncertain information, ruling them out from making optimal decisions. Since agents make decisions based on particular underlying reasons, namely their interests, beliefs then applying logic (by using fuzzy logic) over these reasons can enable agents to refine their decisions and consequently reach better agreements. I refer to this form of negotiation as: Fuzzy logic based negotiation in e-commerce. The contributions of the thesis begin with the use of fuzzy logic to design a reasoning model through which negotiation tactics and strategy are expressed throughout the process of negotiation. Then, an exploration of the differences between this approach and the more traditional bargaining-based approaches is presented. Strategic issues are then explored and a methodology for designing negotiation strategies is developed. Finally, the applicability of the framework is simulated using MATLAB toolbox

Rational bidding using reinforcement learning: an application in automated resource allocation

The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic resource provisioning and usage of computational resources, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a framework for supporting consumers and providers in technical and economic preference elicitation and the generation of bids. Secondly, we introduce a consumer-side reinforcement learning bidding strategy which enables rational behavior by the generation and selection of bids. Thirdly, we evaluate and compare this bidding strategy against a truth-telling bidding strategy for two kinds of market mechanisms – one centralized and one decentralized

Theoretical and Computational Basis for Economical Ressource Allocation in Application Layer Networks - Annual Report Year 1

This paper identifies and defines suitable market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. --Grid Computing

A hybrid model of electronic negotiation : integration of negotiation support and automated negotiation models

Electronic business negotiations are enabled by different electronic negotiation models: automated negotiation models for software agents, negotiation support models for human negotiators, and auction models for both. To date, there is no electronic negotiation model that enables bilateral multi-issue negotiations between a human negotiator and a negotiation agent?an important task in electronic negotiation research. In this thesis, a model is presented that integrates the automated negotiation model and the negotiation support model. The resulting hybrid negotiation model paves the way for human-agent business negotiations. The integration of two models is realised at the levels of negotiation process, communication support and decision making. To this end, the negotiation design, negotiation process, negotiation decision making, and negotiation communication in negotiation support systems (NSSs) and agent negotiation systems (ANSs) are studied and analysed. The analyses on these points help in strengthening the motivation behind hybrid negotiation model and setting aims for the integration of an NSS and an ANS in hybrid negotiation model. We mainly propose a human-agent negotiation design, negotiation process protocols to support the design, a hybrid communication model for human-agent interaction, an agent decision-making model for negotiation with human, and a component for interoperability between NSS and ANS. The agent decision-making model is composed of heuristic and argumentation-based negotiation techniques. It is proposed after analysing different automated negotiation models for different human negotiation strategies. The proposed communication model supports human negotiator and negotiation agent to understand and process negotiation messages from each other. This communication model consists of negotiation ontology, a wrapper agent, and a proper selection of an agent communication language (ACL) and a content language. The wrapper agent plays a role for interoperability between agent system and NSS by providing a communication interface along with the negotiation ontology. The negotiation ontology, ACL and agent content language make the communication model of negotiation agent in ANS. The proposed hybrid model is realised by integrating an ANS into NSS Negoisst. The research aim is to show that a hybrid negotiation system, composed of two heterogeneous negotiation models, can enable human-agent multi-issue integrative negotiations.Elektronische ökonomische Verhandlungen werden durch verschiedene Verhandlungsmodelle ermöglicht: Automatisierte Verhandlungsmodelle für Softwareagenten, Verhandlungsunterstützung für menschliche Verhandelnde und Auktionsmodelle für Beide. Bis heute existiert kein elektronisches Verhandlungsmodell, das bilaterale multi-attributive Verhandlungen zwischen einem menschlichen Verhandelnden und einem Verhandlungsagenten ? eine wichtige Aufgabe in der Forschung im Bereich elektronischer Verhandlungen. In dieser Arbeit wird ein Modell präsentiert, welches das automatisierte Verhandlungsmodell und das Verhandlungsunterstützungsmodell integriert. Das resultierende hybride Verhandlungsmodell ebnet den Weg für ökonomische Mensch-Agent-Verhandlungen. Die Integration der zwei Modelle ist realisiert auf der Ebene von Verhandlungsprozess, Kommunikationsunterstützung und Entscheidungsunterstützung. Dazu werden Verhandlungsdesign, Verhandlungsprozess, verhandlungsbezogene Entscheidungsfindung und Verhandlungskommunikation in Verhandlungsunterstützungssystemen (NSS) und Agentenverhandlungssystemen (ANS) studiert und analysiert. Die Analysen zu diesen Punkten verstärken die Motivation hinter dem hybriden Verhandlungsmodell und bestimmen die Ziele für die Integration von NSS und ANS. Es werden hauptsächlich ein Mensch-Agent-Verhandlungsdesign, Verhandlungsprozessprotokolle zur Unterstützung des Designs, ein hybrides Kommunikationsmodell für Mensch-Agent-Kommunikation, ein Agenten-Entscheidungsmodell für die Verhandlung mit menschlichem Gegenpart und eine Komponente für die Interoperabilität zwischen NSS und ANS. Das Entscheidungsmodell für Agenten besteht aus heuristischen und argumentativen Verhandlungstechniken. Es wird aufgestellt nachdem verschiedene automatisierte Verhandlungsmodelle für verschiedene menschliche Verhandlungsstrategien analysiert worden sind. Die vorgeschlagenen Kommunikationsmodelle unterstützen menschliche Verhandler und Verhandlungsagenten dabei Verhandlungsnachrichten voneinander zu verstehen und zu verarbeiten. Dieses Kommunikationsmodell besteht aus einer Verhandlungsontologie, einem Wrapper-Agenten und einer angemessenen Auswahl der Agentenkommunikationssprache (ACL) und der Inhaltssprache. Der Wrapper-Agent spielt eine Rolle bei der Interoperabilität zwischen dem Agentensystem und dem NSS durch eine Kommunikationsschnittstelle zusammen mit der Verhandlungsontologie. Die Verhandlungsontologie, die ACL und die Inhaltssprache der Agenten ergeben das Kommunikationsmodell der Verhandlungsagenten im ANS. Das vorgestellte hybride Modell ist realisiert als Integration eines ANS in das NSS Negoisst. Das Forschungsziel ist zu zeigen, dass ein hybrides Verhandlungssystem, basierend auf zwei heterogenen Verhandlungsmodellen, integrative multi-attributive Mensch-Agent-Verhandlungen ermöglicht

A hybrid model of electronic negotiation : integration of negotiation support and automated negotiation models

Electronic business negotiations are enabled by different electronic negotiation models: automated negotiation models for software agents, negotiation support models for human negotiators, and auction models for both. To date, there is no electronic negotiation model that enables bilateral multi-issue negotiations between a human negotiator and a negotiation agent?an important task in electronic negotiation research. In this thesis, a model is presented that integrates the automated negotiation model and the negotiation support model. The resulting hybrid negotiation model paves the way for human-agent business negotiations. The integration of two models is realised at the levels of negotiation process, communication support and decision making. To this end, the negotiation design, negotiation process, negotiation decision making, and negotiation communication in negotiation support systems (NSSs) and agent negotiation systems (ANSs) are studied and analysed. The analyses on these points help in strengthening the motivation behind hybrid negotiation model and setting aims for the integration of an NSS and an ANS in hybrid negotiation model. We mainly propose a human-agent negotiation design, negotiation process protocols to support the design, a hybrid communication model for human-agent interaction, an agent decision-making model for negotiation with human, and a component for interoperability between NSS and ANS. The agent decision-making model is composed of heuristic and argumentation-based negotiation techniques. It is proposed after analysing different automated negotiation models for different human negotiation strategies. The proposed communication model supports human negotiator and negotiation agent to understand and process negotiation messages from each other. This communication model consists of negotiation ontology, a wrapper agent, and a proper selection of an agent communication language (ACL) and a content language. The wrapper agent plays a role for interoperability between agent system and NSS by providing a communication interface along with the negotiation ontology. The negotiation ontology, ACL and agent content language make the communication model of negotiation agent in ANS. The proposed hybrid model is realised by integrating an ANS into NSS Negoisst. The research aim is to show that a hybrid negotiation system, composed of two heterogeneous negotiation models, can enable human-agent multi-issue integrative negotiations.Elektronische ökonomische Verhandlungen werden durch verschiedene Verhandlungsmodelle ermöglicht: Automatisierte Verhandlungsmodelle für Softwareagenten, Verhandlungsunterstützung für menschliche Verhandelnde und Auktionsmodelle für Beide. Bis heute existiert kein elektronisches Verhandlungsmodell, das bilaterale multi-attributive Verhandlungen zwischen einem menschlichen Verhandelnden und einem Verhandlungsagenten ? eine wichtige Aufgabe in der Forschung im Bereich elektronischer Verhandlungen. In dieser Arbeit wird ein Modell präsentiert, welches das automatisierte Verhandlungsmodell und das Verhandlungsunterstützungsmodell integriert. Das resultierende hybride Verhandlungsmodell ebnet den Weg für ökonomische Mensch-Agent-Verhandlungen. Die Integration der zwei Modelle ist realisiert auf der Ebene von Verhandlungsprozess, Kommunikationsunterstützung und Entscheidungsunterstützung. Dazu werden Verhandlungsdesign, Verhandlungsprozess, verhandlungsbezogene Entscheidungsfindung und Verhandlungskommunikation in Verhandlungsunterstützungssystemen (NSS) und Agentenverhandlungssystemen (ANS) studiert und analysiert. Die Analysen zu diesen Punkten verstärken die Motivation hinter dem hybriden Verhandlungsmodell und bestimmen die Ziele für die Integration von NSS und ANS. Es werden hauptsächlich ein Mensch-Agent-Verhandlungsdesign, Verhandlungsprozessprotokolle zur Unterstützung des Designs, ein hybrides Kommunikationsmodell für Mensch-Agent-Kommunikation, ein Agenten-Entscheidungsmodell für die Verhandlung mit menschlichem Gegenpart und eine Komponente für die Interoperabilität zwischen NSS und ANS. Das Entscheidungsmodell für Agenten besteht aus heuristischen und argumentativen Verhandlungstechniken. Es wird aufgestellt nachdem verschiedene automatisierte Verhandlungsmodelle für verschiedene menschliche Verhandlungsstrategien analysiert worden sind. Die vorgeschlagenen Kommunikationsmodelle unterstützen menschliche Verhandler und Verhandlungsagenten dabei Verhandlungsnachrichten voneinander zu verstehen und zu verarbeiten. Dieses Kommunikationsmodell besteht aus einer Verhandlungsontologie, einem Wrapper-Agenten und einer angemessenen Auswahl der Agentenkommunikationssprache (ACL) und der Inhaltssprache. Der Wrapper-Agent spielt eine Rolle bei der Interoperabilität zwischen dem Agentensystem und dem NSS durch eine Kommunikationsschnittstelle zusammen mit der Verhandlungsontologie. Die Verhandlungsontologie, die ACL und die Inhaltssprache der Agenten ergeben das Kommunikationsmodell der Verhandlungsagenten im ANS. Das vorgestellte hybride Modell ist realisiert als Integration eines ANS in das NSS Negoisst. Das Forschungsziel ist zu zeigen, dass ein hybrides Verhandlungssystem, basierend auf zwei heterogenen Verhandlungsmodellen, integrative multi-attributive Mensch-Agent-Verhandlungen ermöglicht