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.