Decision Making Methods in Agent Based Modeling (original) (raw)
Decisión Making in Multi-lssue e-Market Auction Using Fuzzy Techniques and Negotiable Attitudes
Journal of theoretical and applied electronic commerce research, 2008
Online auctions are one of the most effective ways of negotiation of salable goods over the internet. Software agents are increasingly being used to represent humans in online auctions. These agents can systematically monitor a wide variety of auctions and can make rapid decisions about what bids to place in what auctions. To be successful in open multi-agent environments, agents must be capable of adapting different strategies and tactics to their prevailing circumstances. This paper presents a software test-bed for studying autonomous bidding strategies in simulated auctions for procuring goods. It shows that agents' bidding strategy explore the attitudes and behaviors that help agents to manage dynamic assessment of prices of goods given the different criteria and scenario conditions. Our agent also uses fuzzy techniques for the decision making: to make decisions about the outcome of auctions, and to alter the agent's bidding strategy in response to the different criteria and market conditions.
Intelligent Agents in an Electronic Auction Context
2000
As business-to-business electronic commerce evolves, different kinds of electronic auctions are expected to become an increasingly common and important way of selling a wide range of products. Therefore, it's very interesting for a Company like Intentia, aiming to be a leading provider of business-to-business (BTB) e-commerce solutions, to investigate how electronic auctions can be integrated into their solutions, and how intelligent agents can be used for this purpose.
Development of a Fuzzy-based Multi-agent System for E-commerce Settings
Procedia Computer Science, 2015
In this paper we present our experience in developing a fuzzy-logic based multi-agent e-commerce system capable of achieving a mutually beneficial deal for the seller and buyer using a negotiation process. We use fuzzy logic to assist users to express their preferences about a product in fuzzy terms such as low, medium and high. Our system evaluates offers based on a fuzzy utility function and feeds utility scores to a fuzzy inference system which then computes its next counter offer. Our paper presents issues involved in the development of a multi-agent system for e-commerce settings using the JADE platform-a modern agent development environment. In this paper our focus is on implementing agents of different types/roles engaged in activities usually encountered with buying and selling in an e-commerce environment. Our concluding remarks and future research are presented.
Auction Advisor: an agent-based online-auction decision support system
Decision Support Systems, 2006
Online auctions are proving themselves as a viable alternative in the C2C and B2C marketplace. Several thousand new items are placed for auction every day and determining which items to bid on or when and where to sell an item are difficult questions to answer for online-auction participants. This paper presents a multiagent Auction Advisor system designed to collect data related to online auctions and use the data to help improve the decision making of auction participants. A simulation of applied Auction Advisor recommendations and a small research study that used subjects making real purchases at online auctions both indicate that online-auction buyers and sellers achieve tangible benefit from the current information acquired by and recommendations made by the Auction Advisor agents. D
Comparison of a Fuzzy-Logic Based Bidding Strategy with Other Strategies in Dynamic Double Auctions
2019
Double auctions are commonly used market mechanisms on the world. Double auctions constitute one of the most complex market mechanisms by allowing both buyers and sellers to make price offers. Complexity theory is an emerging scientific paradigm which deals with complex systems and sometimes called a scientific revolution. One of the main analysis tools in complexity paradigm is agent based simulations. With agent based simulations agent behaviors can be modeled and collective outputs of agent interactions can be obtained from the simulations. Double auctions are complex systems in which buyers and sellers interact with each other. Although double auctions are widely used on the world theoretical works on double auctions are few. Main reason of this is the complexity of double auctions. Complexity theory and agent based simulations promises new opportunities for modeling and understanding double auctions. In this work, we investigated a kind of double auction which is called dynamic...
Agent based e-commerce systems that react to buyers’ feedbacks – A fuzzy approach
International Journal of Approximate Reasoning, 2010
In this paper, we have introduced an agent based e-commerce system which recommends products to buyers as per their preferences. Initially, the agent collects the buyers' preferences in fuzzy or linguistically defined terms and based on this, presents them an ordered set of products. After obtaining the buyers' feedbacks when they actually come across the products, the seller's agent interacts with the buyer (buyer's agent), revises the products preferential order and recommends either the same set of products or a new set of similar products with the revised preferential order. The buyer's revised preferences are taken here as his/her feedback after he/she comes across with the actual products (presented products). Concepts of fuzzy logic and Fuzzy Linear Programming are used here to identify the buyer's feedbacks on the initial presentation of the products. Our methodology also measures the degree of customers' focus on the products which are finally recommended by the e-commerce agent. The product ranking obtained through buyers' initial preferences is considered here as his/her subjective information and the available information from the agents' presented products are taken as the objective information.
Buyer agent decision process based on automatic fuzzy rules generation methods
International Conference on Fuzzy Systems, 2010
Software Agents can assume the responsibility of finding and negotiating products on behalf of their owners in an electronic marketplace. In such cases, Fuzzy Logic can provide an efficient reasoning mechanism especially for the buyer side. Agents representing buyers can rely on a fuzzy rule base in order to reason for their next action at every round of the interaction process with sellers. In this paper, we describe a model where the buyer builds its fuzzy knowledge base using algorithms for automatic fuzzy rules generation based on data provided by experts and compare a set of such algorithms. Owing to such algorithms, agent developers spend less time and effort for the definition of the underlying rule base. Moreover, the rule base is efficiently created through the use of the dataset indicating the behaviour of the buyer and, thus, representing its line of actions in the electronic marketplace. In our work, we use such algorithms for the definition of the buyer behaviour and we provide critical insides for every algorithm describing their advantages and disadvantages. Moreover, we present numerical results for every basic parameter of the interaction process, such as the time required for the rule base generation, the Joint Utility of the interaction process or the value of the acceptance degree that each algorithm results.
Electronic Auction with autonomous intelligent agents: Finding opportunities by being there
Ibm Journal of Research and Development, 2001
The overwhelming options conveyed by Internet exaggerated growth bring new issues for users engaged in buying and/or selling goods using the net as the business medium. Goods and services can be exchanged, directly sold or negotiated in auctions. In any of these situations, finding the required product by the right price is the big challenge for Internet users. Especially in e-auction, timing and strategic actions are vital to a successful deal. In this paper, we propose a model for e-auction based on intelligent agents technology. The use of agents make possible to reflect better what happens in real auctions. Agents act together with buyers, sellers and auctioneers to assist them obtaining the best deal or at least finding Nash equilibrium point.
Building an agent-mediated electronic commerce system with decision analysis features
Decision Support Systems, 2001
This paper describes a web-based electronic commerce system in which customers and merchants delegate the related tasks to their personal software agents. Messages passed between these agents can fully encapsulate the associated parties' points of view towards a market transaction. More specifically, an offer request consists of a list of the product attributes the customer wants to know about, a partial order of their importance, and the constraints imposed. On the other side, an offer proposal can be tailored according to the information conveyed in the corresponding offer request. Advanced features of the system include the permanent existence of our agents in the market, thus being able to learn from it, their ability to act proactively in order to initiate a transaction, and the integration of an interactive multiple criteria decision-making tool, with which a buying agent performs a comparative evaluation of the proposals in a semi-autonomous way. q
Designing bidding strategies for trading agents in electronic auctions
Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160), 1998
Auction-based electronic commerce is an increasingly interesting domain for developing trading agents. In this paper we present our first contributions towards the construction of such agents by introducing both a formal and a more pragmatical approach for the design of bidding strategies that provide buyer agents with useful heuristic guidelines to participate in auction-based tournaments. On the one hand, our formal view relies on possibilistic-based decision theory as the means of handling possibilistic uncertainty on the consequences of actions due to the lack of knowledge about the other agents' behaviour. On the other hand, for practical reasons we also propose a twofold method for decision making that does not require the evaluation of the whole set of alternative actions. This approach utilizes global (market-centered) probabilistic information in a first decision step which is subsequently refined by a second decision step based on the individual (rival-centered) possibilistic information induced from the memory of cases composing the history of tournaments. In this way, the resulting bidding strategy balances the agent's short-term benefits, related to the probabilistic information, with its long-term benefits, related to the possibilistic information.
An adaptive bidding agent for multiple English auctions: a neuro-fuzzy approach
2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542)
This paper presents the design, implementation and evaluation of a novel bidding strategy for obtaining goods in multiple overlapping English auctions. The strategy uses fuzzy sets to express trade-offs between multi-attribute goods and exploits neuro-fuzzy techniques to predict the expected closing prices of the auctions and to adapt the agent's bidding strategy to reflect the type of environment in which it is situated. We show, through empirical evaluation against a number of methods proposed in the multiple auction literature, that our strategy performs effectively and robustly in a wide range of scenarios.
A Classification of Auction Mechanism : Potentiality for Multi-Agent System ( MAS ) Based Modeling
2006
What are auctions and how are they applicable in Multi-agent systems (MAS). This study reviews the various auction mechanisms such as forward auctions, reverse auctions, and double auctions, along with the roots of the newer auctions that have been evolved over time. Subsequently, a classification of various auction mechanism are presented that will enable us to get a perspective on how auctions have evolved and thereby a better understanding on how to incorporate these mechanism into a MAS. Later, important auction properties are compared with the auction mechanism to get a better grasp of what a particular action might possess as strength and its related weakness. Auction mechanism have been applied in agent based modeling. This study illustrates the comprehensive set of current and emerging auctions mechanism that have the potentially to be tested through agent based modeling as well as serve as a basis for further development of Multi-agent systems.
Designing Intelligent Software Agents for Auctions with Limited Information Feedback
Information Systems Research, 2009
T his paper presents analytical, computational, and empirical analyses of strategies for intelligent bid formulations in online auctions. We present results related to a weighted-average ascending price auction mechanism that is designed to provide opaque feedback information to bidders and presents a challenge in formulating appropriate bids. Using limited information provided by the mechanism, we design strategies for software agents to make bids intelligently. In particular, we derive analytical results for the important characteristics of the auction, which allow estimation of the key parameters; we then use these theoretical results to design several bidding strategies. We demonstrate the validity of designed strategies using a discrete event simulation model that resembles the mechanisms used in treasury bills auctions, business-to-consumer (B2C) auctions, and auctions for environmental emission allowances. In addition, using the data generated by the simulation model, we show that intelligent strategies can provide a high probability of winning an auction without significant loss in surplus.
Using an Active Fuzzy Eca Rule-Based Negotiation Agent in E-Commerce
E-commerce is considered a key service within modern information society, and the idea of automating e-commerce transactions has attracted much interest in recent years. A multi-agent model is a system that applies various autonomous agents to accomplish specified goals. Such a system addresses resource allocation issues. Because the nature of resource trading requires multiple agents to request geographically dispersed heterogeneous resources, we use a multi-agent architecture for e-commerce because each agent can be describe each participant intelligently. In this paper, negotiation agents based on fuzzy ECA rule-based proposed. Here we focus on agents in e-commerce that negotiate between sellers and buyers in order to get the best deal. The negotiation process between buyers and its sellers begins through combined and fairness protocols. We add learning properties to agents based on a fuzzy decision tree to develop negotiation skills and present the results. Using a fuzzy decisio...
Economic Effects of Multiple Intelligent Agents in Online Auctions
Online auction mechanism has enriched the trading community. It brings together both sellers and buyers from around the world without the geographical limitations and time constraints. In this paper, an auction market is simulated with multiple English auctions that are running concurrently consisting of human bidders and intelligent agents with various bidding strategies. For the analysis, we considered the market economy such as the auction closing price trend and the number of auctions that were closed successfully. We also studied a situation where a market is fully populated by different types of intelligent agents. Based on the results obtained, we discovered that bidders received more surplus and they are more satisfied when they are using bidder agents rather than bidding in the auctions themselves. From the seller's perspective, they may not welcome these bidder agents since their revenues are reduced in a market with finite number of auctions and participants.
2013
Abstract: The main goal of the research that preliminary results have been presented in this paper is to develop an agent–oriented electronic marketplace for modeling and simulation of dynamic pricing models, i.e. models in which the price of the item is allowed to fluctuate as supply and demand in a market change. The work provides an overview of forms of dynamic pricing models, with particular emphasis on auctions. After that, the main rationale behind using Multi-agent Systems approach for modeling and simulation of complex business structures has been shown. Then the development process of an electronic marketplace, including agents ’ architecture as well as implementation environment selection, structure and business logic of e-marketplace have been presented. Last part of the paper comprises conclusions and further research plans.
Paradigm for Agent Selection in B 2 C E-Commerce
2019
Multi agent system (MAS) model has been extensively used in the different tasks of E-Commerce such as customer relation management (CRM), negotiation and brokering. The objective of this paper is to evaluate a seller agent’s various cognitive parameters like capability, trust, and desire. After selecting a best seller agent from ordering queue, it applies negotiation strategies to find the most profitable proposal for both buyer and seller. This mechanism belongs to a semi cooperative negotiation type, and selecting a seller and buyer agent pair using mental and cognitive parameters. This work provides a logical cognitive model, logical negotiation model between buyer agent and selected seller agent. dination, good communication and negotiation with other agents (Jennings et al., 2003). Hence the software agent should be autonomous, reactive and proactive. Multi agent system (MAS) model has been extensively used in the different tasks of E-Commerce such as CRM, negotiation and broke...
2012
The main goal of the research that preliminary results have been presented in this paper is to develop an agent–oriented electronic marketplace for modeling and simulation of dynamic pricing models, i.e. models in which the price of the item is allowed to fluctuate as supply and demand in a market change. The work provides an overview of forms of dynamic pricing models, with particular emphasis on auctions. After that, the main rationale behind using Multi-agent Systems approach for modeling and simulation of complex business structures has been shown. Then the development process of an electronic marketplace, including agents’ architecture as well as implementation environment selection, structure and business logic of e-marketplace have been presented. Last part of the paper comprises conclusions and further research plans.
A Fuzzy Approach for Bidding Strategy Selection
Cybernetics and Information Technologies, 2000
The goal of this work is to explore the applicability of fuzzy logic in multiagent systems for choosing the best bidding strategy in electronic auction. To find the multi-criterion ordering, agents use a fuzzy algorithm ARAKRI2 with direct aggregation operators MaxMin and MinAvg. The key difference between this new approach and known from the literature solution FTNA is in the lack of weighted coefficients. Despite the difference both algorithms give results that are similar. Therefore, the proposed approach can successfully solve the task for multi criteria selection of bidding strategy.
Automatic price negotiation on the web: An agent-based web application using fuzzy expert system
Expert Systems with Applications, 2011
A traditional internet auction is restricted by the limitation of time. It is necessary to conduct an internet auction in a certain time period. The final trading price is determined until this certain period ends. This study improves this situation by removing the time limitation. Based on the fuzzy inference theory, this paper proposes an agent-based price negotiation system for on-line auctions. Mainly, three agents are used in the study: a seller agent, a buyer agent, and a mediator agent. The proposed system provides an easy-to-use environment and good customizability for users (buyers or sellers) to customize their price negotiation strategies using user-defined fuzzy rules. The final negotiated price is immediately determined after the buyer sends his bids to the proposed system. This study develops a Java-based computer package to implement the price negotiation system where Model-View-Controller (MVC) design pattern is employed in design of the package. Unified Modeling Language (UML) is also utilized to describe the structures and behaviors of the package. To validate the proposed system, this study built an on-line auction website with the proposed price negotiation mechanism for internet users to buy or sell their merchandises. An evaluation was finally conducted to investigate the users' satisfaction with the proposed system. Briefly, the proposed system is featured by: (1) instantly getting negotiated price without waiting; (2) conducting price negotiation at any time; (3) determining strategy rules easily, and (4) using customizable negotiation strategies defined by users.