Foundations of Human-Aware Planning -- A Tale of Three Models

abstract: A critical challenge in the design of AI systems that operate with humans in the loop is to be able to model the intentions and capabilities of the humans, as well as their beliefs and expectations of the AI system itself. This allows the AI system to be "human- aware" -- i.e. the human task model enables it to envisage desired roles of the human in joint action, while the human mental model allows it to anticipate how its own actions are perceived from the point of view of the human. In my research, I explore how these concepts of human-awareness manifest themselves in the scope of planning or sequential decision making with humans in the loop. To this end, I will show (1) how the AI agent can leverage the human task model to generate symbiotic behavior; and (2) how the introduction of the human mental model in the deliberative process of the AI agent allows it to generate explanations for a plan or resort to explicable plans when explanations are not desired. The latter is in addition to traditional notions of human-aware planning which typically use the human task model alone and thus enables a new suite of capabilities of a human-aware AI agent. Finally, I will explore how the AI agent can leverage emerging mixed-reality interfaces to realize effective channels of communication with the human in the loop.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Human-Robot Teams – Paving the Way for the Teams of the Future

Thanks to advances in artificial intelligence and robotics, robots, and especially social robots that can naturally interact with humans, are now found in more and more areas of our lives. At the same time, teams have been the norm in organizations for decades. To bring these two circumstances together, this dissertation addresses the use of social robots together with humans in teams, so-called human-robot teams (HRTs). This work aims to advance knowledge about HRTs and important underlying mechanisms in the establishment of such teams, thereby providing insights in two aspects. First, a structured and universal definition of HRTs is derived from the various perspectives of extant research, and based on a comprehensive literature overview, important characteristics and influencing factors of HRTs as well as research gaps in HRT research are identified. Second, insights into the underlying mechanisms of the establishment of human-robot teams are provided for settings with social robots in two different team roles: team assistant and lower-level (team) manager. For this purpose, this dissertation contains three research studies that cover the currently largely unexplored area of social robots' use in organizational teams at both the employee and lower-level manager levels. The first study (conceptual study) provides a foundation for this dissertation and beyond by developing a structured and universal definition of HRTs. It also structures extant research on HRTs and proposes an agenda for future research on HRTs based on research gaps identified in a comprehensive literature review that includes 194 studies on HRTs. The second and third studies (empirical studies 1 and 2) use empirical online studies to address two of the research gaps identified in the conceptual study. They examine the underlying mechanisms in decisions for social robots in two different team roles: team assistant (empirical study 1) and team manager (empirical study 2). By looking at expectations and experiences of taskwork-/performance-related and teamwork-related/relational features of social robots using polynomial regressions and response surface analyses, these studies rely on expectation disconfirmation theory to provide a detailed investigation of the underlying mechanisms of organizational decisions for social robots. Empirical study 1 thereby shows that for teamwork, positive disconfirmation and high levels of experiences lead to higher acceptance of humanoid and android robotic team assistants, and similar results emerge for a humanoid robot’s taskwork skills. In contrast, for taskwork skills of android team assistants, high levels of positive disconfirmation lead to lower robot acceptance. For robotic lower-level managers, empirical study 2 shows that there are discrepancies in the evaluation of performance-related usefulness and relational attitude. While for usefulness a slight overfulfilment of expectations leads to a positive impact on the readiness to work with, before evaluations decrease with greater overfulfillment, for attitude increasing positive experiences are associated with (decreasing) positive evaluations of readiness. In summary, this dissertation contributes to scientific research on HRTs by advancing the understanding of HRTs, providing a structured and universal definition of HRTs, and suggesting avenues for future research. The systematic investigation of underlying mechanisms for the selection of different types of social robots for different team roles provides a holistic view of this new form of organizational teams. In addition to the research contributions, this thesis also provides practical guidance for the successful establishment of HRTs in organizations