—In an agent-based online auction system, a bidding agent can automatically place bids on behalf of a human user according to a user-specified bidding strategy. Current implementations of bidding agents only support a set of simple predefined bidding strategies. In this paper, we introduce a formal bidding strategy model that supports specification of complex bidding strategies for autonomous bidding agents. The formal model is defined as a layered bidding strategy model (LBSM), which can be represented using notations adapted from UML activity diagrams. For real-time and efficient reasoning, the formal model is converted into a rule-based bidding strategy model (RBSM) represented in bidding strategy language (BSL), which can be directly executed by a reasoning module of an autonomous bidding agent. We present an algorithm for converting an LBSM to a rule-based bidding strategy model, and an algorithm to drive the reasoning engine. Finally, we develop a prototype agent-based online auction system using JADE, and demonstrate how layered bidding strategies can be precisely specified, and how our approach may support analysis of impacts on bidding histories by using different bidding strategies in agent-based online auctions.
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