Incorporating emotions into automated negotiation

Proceedings of the …, 2009

Negotiation is a daily occurring process at all levels of society. Emotion plays an important role in negotiation between humans. In this paper we discuss to what extent and in which form ICT techniques can be used to get a grip on the emotional processes that play a role during negotiations. We focus on emotion recognition and measurement. Our analysis shows that current emotion recognition & measurement technology is mainly usable in the preparation for negotiations (including training sessions) and during offline moments of the negotiation (e.g., time-outs). The main arguments for this conclusion are: (1) valid and reliable emotion recognition and measurement techniques are usually invasive, and, (2) it is unclear if participants in a negotiation accept the technology.

2011

ABSTRACT There is now considerable evidence in social psychology, economics, and related disciplines that emotion plays an important role in negotiation. For example, humans make greater concessions in negotiation to an opposing human who expresses anger, and they make fewer concessions to an opponent who expresses happiness, compared to a no-emotion-expression control.

2020

Social agents within Intelligent Learning Environments can enhance their own abilities by interacting to reach agreements and carrying them out. The typical reasoning process that directs agents to rejection or acceptance of these agreements is negotiation. In broad terms, an agreement is a series of conditions and commitments accepted by the parties involved that may refer to a future action plan, an exchange of articles, or assignment of tasks and roles. This article is aimed at proposing a negotiating agent that manifests realistic reactions resulting from forming emotional relationships that reflect in their interactions the characteristics of their personality and their emotional state. To this end, the use of negotiations in the development of social activities, some approaches for the implementation of negotiations between agents and software for the implementation of these agents are addressed. To conclude, the proposal of an agent that includes personality and emotions in t...

Cognitive Technologies, 2012

The development of proficient automated agents has flourished in recent years, yet making the agents interact with people has still received little attention. This is mainly due to the unpredictable nature of people and their negotiation behavior, though complexity and costs attached to experimentation with people, starting from the design and ending with the evaluation process, is also a factor. Even so, succeeding in designing proficient automated agents remains an important objective. In recent years we have invested much effort in facilitating the design and evaluation of automated agents interacting with people, making it more accessible to researchers. We have created two distinct environments for bargaining agents, as well as proposing a novel approach for evaluating agents. These are key factors for making automated agents become a reality rather than remain theoretical.

To date, a variety of automated negotiation agents have been created. While each of these agents has been shown to be effective in negotiating with people in specific environments, they lack natural language processing (NLP) methods required to enable real-world types of interactions. In this paper we study how existing agents must be modified to address this limitation. After performing an extensive study of agents' negotiation with human subjects, we found that simply modifying existing agents to include an NLP module is insufficient to create these agents. Instead the agents' strategies must be modified to address partial agreements and issue-by-issue interactions.

Studies in Computational Intelligence, 2011

Motivated by the challenges of bilateral negotiations between people and automated agents we organized the first automated negotiating agents competition (ANAC 2010). The purpose of the competition is to facilitate the research in the area bilateral multi-issue closed negotiation. The competition was based on the Genius environment, which is a General Environment for Negotiation with Intelligent multi-purpose Usage Simulation. The first competition was held in conjunction with the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-10) and was comprised of seven teams. This paper presents an overview of the competition, as well as general and contrasting approaches towards negotiation strategies that were adopted by the participants of the competition. Based on analysis in post-tournament experiments, the paper also attempts to provide some insights with regard to effective approaches towards the design of negotiation strategies.

2009

Research on automated negotiators has flourished in recent years. Yet, most of the time, the research does not focus on automated negotiators capable of negotiating efficiently with people. Many challenges are facing agents designers who aim to design an automated negotiator, even when people are not in the loop. In addition, the fact that people are scarce resources makes the validation process of the efficacy of the automated negotiators an exhausting task. Yet, these challenges can be overcome. By reviewing existing automated negotiators and reporting on experiments we conducted with automated negotiators, we shed some light on how these challenges can be overcome, and thus motivate other researchers to pursue this exciting line of research.

To date, a variety of automated negotiation agents have been created. While each of these agents has been shown to be effective in negotiating with people in specific environments, they lack natural language processing support required to enable real-world types of interactions. In this paper we present NegoChat, the first negotiation agent that successfully addresses this limitation. NegoChat contains several significant research contributions. First, we found that simply modifying existing agents to include an NLP module is insufficient to create these agents. Instead, the agents' strategies must be modified to address partial agreements and issue-byissue interactions. Second, we present NegoChat's negotiation algorithm. This algorithm is based on bounded rationality, and specifically Aspiration Adaptation Theory (AAT). As per AAT, issues are addressed based on people's typical urgency, or order of importance. If an agreement cannot be reached based on the value the human partner demands, the agent retreats, or downwardly lowers the value of previously agreed upon issues so that a "good enough" agreement can be reached on all issues. This incremental approach is fundamentally different from all other negotiation agents, including the state-of-the-art KBAgent. Finally, we present a rigorous evaluation of NegoChat, showing its effectiveness.

CHI '07 Extended Abstracts on Human Factors in Computing Systems, 2007

This paper investigates the manner in which decisionmaking is influenced by the impressions given by lifelike agents in negotiation situations. These impressions comprise an agent's facial expressions such as happy and sad, and the history of relationship with the agent. In this paper, we introduce a negotiation game as one of the basic interactions based on the soft game theory. The experimental results reveal that expressions and history significantly influence the receiver's impressions and decision-making. The findings of this study can be beneficial for designing the nonverbal expressions of an animated agent who can negotiate and make a deal with users.

Negotiation Journal

Recognition of the role played by emotions in negotiation is growing. This article synthesizes current research around four broad themes: moves and exchanges, information processing, social interaction, and context. The authors' review reveals that much of the research on this topic has focused on two key emotions, anger and happiness. More recently, negotiators have turned to other emotions such as guilt and disappointment, demonstrating that not all negative emotions have the same consequences, or activate the same regions of the brain. Focusing on social interaction, the authors note that negotiators may influence each others' emotions: whether negotiators converge to anger or happiness has different consequences for agreement. Researchers have broadened their examination of emotion by considering how external factors such as power, the number of negotiators, culture, and gender influence the impact of emotional expression. The authors also consider the function and impac...