Designing an Intelligent Agent that Negotiates Tactfully with Human Counterparts: A Conceptual Analysis and Modeling Framework

Automated negotiation has attracted growing interest within fields such as e-business, multi-agent systems, and web services. Nevertheless, a majority of automated negotiation research concentrates on tactics for pure agent-agent interaction, which may not be applicable in today's e-business environment involving human decision makers. We argue that the design of negotiation agents should consider possible participation of human counterparts, thus requiring more sophisticated machine intelligence in strategic decision making. This paper provides a conceptual analysis of negotiation strategies and tactics from psychological and behavioral literature, and proposes a novel set of tactics for building collaborative agents. These tactics - multiple equivalent (simultaneous) offers, monotone decreasing concession, and strategic decision delay - are posited to enhance some aspects of negotiation outcomes without sacrificing others. Furthermore, we present a modeling framework that translates these tactics into computational rules for prototype development. The implications and future research opportunities are discussed.