Automated negotiation for e-commerce decision making: A goal deliberated agent architecture for multi-strategy selection

a r t i c l e i n f o Automated negotiation plays an important role in dynamic trading in e-commerce. Its research largely focuses on negotiation protocol and strategy design. There is a paucity of further scientific investigation and a pressing need on the implementation of multi-strategy selection, which is crucially useful in human–computer negotiation to achieve better online negotiation outcomes. The lack of such studies has decelerated the process of applying automated negotiation to real world problems. To address the critical issue, this paper develops a multi-strategy negotiating agent system. More specifically, we formally define the agent's conceptual model, and design its abstract software architecture. Grounded on the integration of the time-dependent and behavior-dependent tactics, we also develop a multi-strategy selection theoretical model and algorithm. To demonstrate the effectiveness of this model algorithm, we implement a prototype and conduct numerous experiments. The experimental analysis not only confirms our model's effectiveness but also reveals some insights into future work about human–computer negotiation systems, which will be widely used in the future B2C e-commerce. Negotiation is a communication process among a group of parties with conflicting interests or preferences in order to reach an agreement or compromise [1,2]. The tremendous success of the online auction [3], which is a kind of one-to-many negotiation and has been employed as the main trading mechanism in the electronic market and smart market [4], suggests that the dynamic trading based on e-negotiation has gradually become the primary paradigm of decision making in e-commerce [5–8]. In addition, e-commerce oriented negotiation is increasingly assuming a pivotal role in many organizations, and a number of prominent negotiation models have been developed over the past decades [9]. There are three forms of e-commerce oriented negotiation [2]: human–human negotiation, computer–computer negotiation, and human–computer negotiation. With the rapid growth of global e-markets, there has been a significant interest in designing Automated Negotiation System (ANS) [10] that can serve as surrogates for human business decision-makers, where software agents are designed to autonomously act on behalf of the real-world parties [11,12]. As the automated negotiation is becoming crucially important and pervasive and agents promise exciting opportunities to turn conventional transactions into an automated, cost-efficient manner, the study of ANS has piqued increasing interest in the scholarly fields of e-commerce and artificial intelligence [13]. While the e-commerce and AI literatures mirror that the ANS can be used in computer–computer and human–computer negotiations, …