This paper analyzes the automated negotiation process between two competitive agents in an alternating offers negotiation model. Generally speaking, the outcome of a negotiation depends on some parameters—the agents’ reservation prices, their attitude toward time and the strategies they use, etc. | Journal of Automation and Control Engineering Vol. 4, No. 4, August 2016 Optimal Strategies for Agents in an Alternating Offers Negotiation Protocol Considering Time Constraint Linlan Zhang and Huaming Gui School of Business, Hubei University, Wuhan, China E-mail: misalinlan9904@ Abstract—This paper analyzes the automated negotiation process between two competitive agents in an alternating offers negotiation model. Generally speaking, the outcome of a negotiation depends on some parameters—the agents’ reservation prices, their attitude toward time and the strategies they use, etc. In most realistic situations, it is not possible for agents to have complete information about all these parameters for its opponent. However, it is general for agents to have partial information about these parameters for its opponent. Under such uncertain situation, our aim is to determine how an agent can exploit the available information in selecting an optimal strategy which maximizes its expected utility. Here, in particular, the optimal strategies are determined considering time constraint. Moreover, we set the concession constraints for each agent to assure the negotiation process is continually shortened. This design can assist researchers in AI (Artificial Intelligence) to construct software agents, where these intelligent agents can optimally negotiate on behalf of users in a given state of knowledge and context. Index Terms—automated negotiation, time constraint, alternating offer, optimal strategy I. INTRODUCTION With rapid growth of electronic commerce, autonomous agents can play an increasing variety of roles in an automated negotiation system. Humans seldom negotiate effectively during negotiation process owing to limited information-processing capabilities [1] and biases [2]. Thus, automated negotiation has become an important research subject in the artificial intelligence (AI) field and economics field. Many studies have been done to solve this challenge .
