Increasing Bid Expressiveness for Effective and Balanced E-Barter Trading

Abstract

Abstract. We present a novel knowledge-based approach for automated electronic barter trade systems. An e-barter is basically a closed e-marketplace, where agents may exchange (buy/sell) goods -or equivalent trade dollars-only with other participants to the e-barter. Obviously, in such systems one of the major issues is keeping exchanges as balanced as possible. If the description of goods or services to be exchanged is simple and limited to a well defined set, e.g., oil, wheat, transport, etc., then an exchange based only on price and quantity is enough. But, what if goods or services to be exchanged are described in a complex way? Is it a suitable exchange the one involving mobile phones supporting video streaming with a QWERTY keyboard if the agent is looking for smart phones? Those two descriptions, although very different form a syntactic point of view, are very similar with respect to their meaning (semantics). How could an agent manage and exploit the knowledge on a given domain to deal with such a semantic information and optimize exchanges?We focus on how to find most promising matches, in a many-to-many matchmaking process, between bids (supplies/demands), taking into account not only the price and quantities as in classical barter trade systems, but also a semantic similarity among bid descriptions while keeping exchanges balanced.To this aim we use a logical language to express agent preferences, thereby enhancing bid expressiveness. We also define a logic-based utility function that allows to evaluate the semantic similarity between bids. Finally we illustrate the optimization problem we solve in order to clear the market.

Development of Semantic Web-Enabled BDI Multi-Agent Systems Using SEA_ML: An Electronic Bartering Case Study

“…Ragone et al [69] focused on E-barter systems with a new knowledge-based approach in their study. The goal is to ensure that multiple barter situations are performed with optimal matching.…”

“…In this study, a logical language was introduced that provides more complex specifications of agents' requests. It is also intended to simulate the semantic similarity between proposals that will be presented in a logic-based utility function [69]. On the other hand, in [70], a game concept was defined to describe the interactions in the barter system.…”

“…The studies presented in [69,70] focuses on improving the matching mechanism for bartering using more specific parameters in the definition of requirements and logic-based utility functions.…”

Peer-to-Peer Bartering: Swapping Amongst Self-interested Agents

“…• The use of ontologies: How could an agent manage and exploit the knowledge on a given domain to deal with such semantic information and optimise exchanges? [147] -The use of a logical language to express agent preference.…”