Emmanuel Johnson

Emmanuel Johnson
University of Southern California | USC · Department of Computer Science

BS in Computer Engineering, MSc in Robotics

About

17
Publications
25,522
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115
Citations
Introduction
I'm interested in building automated agents that can be used to teach negotiation. In accomplishing this goal, my work looks at developing techniques for automated agents to understand a human's negotiation strategy and provide personalized feedback based on their performance.

Publications

Publications (17)
Conference Paper
Machine learning (ML) can in theory be used to personalize educational content by identifying online activities aligned with learners' interests. Yet, are learners' self-reported ratings of activities associated with a machine learning generated recommender score? In the current study we sought to address this question using learner's ratings of ac...
Article
Artificial intelligence (AI), machine learning (ML), affective computing, and big‐data techniques are improving the ways that humans negotiate and learn to negotiate. These technologies, long deployed in industry and academic research, are now being adopted for educational use. We describe several systems that help human negotiators evaluate and le...
Article
Full-text available
Negotiation is an integral part of our daily lives regardless of occupation. Although ubiquitous to our experience, we are never taught to negotiate. This lack of training presents many consequences from unfair salary negotiation to geopolitical ramification. The ability to resolve conflicts and negotiate is becoming more critical due to the rise o...
Conference Paper
Full-text available
Recent research shows that how we respond to other social actors depends on what sort of mind we ascribe to them. In this article we examine how perceptions of a virtual agent's mind shape behavior in human-agent negotiations. We varied descriptions and communicative behavior of virtual agents on two dimensions according to the mind perception theo...
Conference Paper
Research has shown that virtual agents can be effective tools for teaching negotiation. Virtual agents provide an opportuni-ty for students to practice their negotiation skills which leads to better outcomes. However, these negotiation training agents often lack the ability to understand the errors students make when negotiating, thus limiting thei...
Chapter
Intelligent tutoring systems have proven very effective at teaching hard skills such as math and science, but less research has examined how to teach “soft” skills such as negotiation. In this paper, we introduce an effective approach to teaching negotiation tactics. Prior work showed that students can improve through practice with intelligent nego...
Conference Paper
This work explores whether culture impacts the extent to which social dialogue can mitigate (or exacerbate) the loss of trust caused when agents make conversational errors. Our study uses an agent designed to persuade users to agree with its rankings on two tasks. Participants from the U.S. and Japan completed our study. We perform two manipulation...
Chapter
Full-text available
Research has found that individuals can improve their negotiation abilities by practicing with virtual agents [1, 2]. For these pedagogical agents to become more “intelligent,” the system should be able to give feedback on negotiation performance [3, 4]. In this study, we examined the impact of providing such individualized feedback. Participants f...
Conference Paper
Full-text available
In this paper, we explore the potential of regulatory focus theory as a framework for personalizing human-machine interactions. We manipulate framing (gain or loss) of a collaborative word-guessing game where a fully-automated virtual human gives clues. Consistent with previous work on regulatory focus, we find evidence of significantly higher perc...
Conference Paper
Full-text available
This work explores the extent to which social dialogue can mitigate (or exacerbate) the loss of trust caused when robots make conversational errors. Our study uses a NAO robot programmed to persuade users to agree with its rankings on two tasks. We perform two manipulations: (1) The timing of conversational errors - the robot exhibited errors eithe...
Conference Paper
Social robots establish rapport with human users. This work explores the extent to which rapport-building can benefit (or harm) conversations with robots, and under what circumstances this occurs. For example, previous work has shown that agents that make conversational errors are less capable of influencing people than agents that do not make erro...
Conference Paper
Full-text available
Although negotiation is an integral part of daily life, most people are unskilled negotiators. To improve one's skill set, a range of costly options including self-study guides, courses, and training programs are offered by various companies and educational institutions. For those who can't afford costly training options, virtual role playing agent...
Conference Paper
Full-text available
We demonstrate two agents, a robot and a virtual human, which can be used for studying factors that impact social influence. The agents engage in dialogue scenarios that build familiarity, share information, and attempt to influence a human participant. The scenarios are variants of the classical “survival task,” where members of a team rank the im...

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Projects (2)