Multiple theories of problem-solving hypothesize that there are distinct qualitative phases exhibited during effective problem-solving. However, limited research has attempted to identify when transitions between phases occur. We integrate theory on collaborative problem-solving with dynamical systems theory suggesting that when a system is undergoing a phase transition it should exhibit a peak in entropy and that entropy levels should also relate to team performance. Communications from 40 teams that collaborated on a complex problem were coded for occurrence of problem-solving processes. (...) We applied a sliding window entropy technique to each team's communications and specified criteria for identifying data points that qualify as peaks and determining which peaks were robust. We used multilevel modeling, and provide a qualitative example, to evaluate whether phases exhibit distinct distributions of communication processes. We also tested whether there was a relationship between entropy values at transition points and CPS performance. We found that a proportion of entropy peaks was robust and that the relative occurrence of communication codes varied significantly across phases. Peaks in entropy thus corresponded to qualitative shifts in teams’ CPS communications, providing empirical evidence that teams exhibit phase transitions during CPS. Also, lower average levels of entropy at the phase transition points predicted better CPS performance. We specify future directions to improve understanding of phase transitions during CPS, and collaborative cognition, more broadly. (shrink)

The growing field of machine morality has becoming increasingly concerned with how to develop artificial moral agents. However, there is little consensus on what constitutes an ideal moral agent let alone an artificial one. Leveraging a recent account of heroism in humans, the aim of this paper is to provide a prospective framework for conceptualizing, and in turn designing ideal artificial moral agents, namely those that would be considered heroic robots. First, an overview of what it means to be an (...) artificial moral agent is provided. Then, an overview of a recent account of heroism that seeks to define the construct as the dynamic and interactive integration of character strengths and situational constraints that afford the opportunity for moral behavior . With this as a foundation, a discussion is provided for what it might mean for a robot to be an ideal moral agent by proposing a dynamic and interactive connectionist model of robotic heroism. Given the limited accounts of robots engaging in moral behavior, a case for extending robotic moral capacities beyond just being a moral agent to the level of heroism is supported by drawing from exemplar situations where robots demonstrate heroism in popular film and fiction. (shrink)

In this paper we suggest that differing approaches to the science of social cognition mirror the arguments between radical embodied and traditional approaches to cognition. We contrast the use in social cognition of theoretical inference and mental simulation mechanisms with approaches emphasizing a direct perception of others’ mental states. We build from a recent integrative framework unifying these divergent perspectives through the use of dual-process theory and supporting social neuroscience research. Our elaboration considers two complementary notions of direct perception: one (...) primarily stemming from ecological psychology and the other from enactive cognition theory. We use this as the foundation from which to offer an account of the informational basis for social information and assert a set of research propositions to further the science of social cognition. In doing so, we point out how perception of the minds of others can be supported in some cases by lawful information, supporting direct perception of social affordances and perhaps, mental states, and in other cases by cues that support indirect perceptual inference. Our goal is to extend accounts of social cognition by integrating advances across disciplines to provide a multi-level and multi-theoretic description that can advance this field and offer a means through which to reconcile radical embodied and traditional approaches to cognitive neuroscience. (shrink)

Complex work in teams requires coordination across team members and their technology as well as the ability to change and adapt over time to achieve effective performance. To support such complex interactions, recent efforts have worked toward the design of adaptive human-autonomy teaming systems that can provide feedback in or near real time to achieve the desired individual or team results. However, while significant advancements have been made to better model and understand the dynamics of team interaction and its relationship (...) with task performance, appropriate measures of team coordination and computational methods to detect changes in coordination have not yet been widely investigated. Having the capacity to measure coordination in real time is quite promising as it provides the opportunity to provide adaptive feedback that may influence and regulate teams’ coordination patterns and, ultimately, drive effective team performance. A critical requirement to reach this potential is having the theoretical and empirical foundation from which to do so. Therefore, the first goal of the paper is to review approaches to coordination dynamics, identify current research gaps, and draw insights from other areas, such as social interaction, relationship science, and psychotherapy. The second goal is to collate extant work on feedback and advance ideas for adaptive feedback systems that have potential to influence coordination in a way that can enhance the effectiveness of team interactions. In addressing these two goals, this work lays the foundation as well as plans for the future of human-autonomy teams that augment team interactions using coordination-based measures. (shrink)

Complex work in teams requires coordination across team members and their technology as well as the ability to change and adapt over time to achieve effective performance. To support such complex interactions, recent efforts have worked toward the design of adaptive human-autonomy teaming systems that can provide feedback in or near real time to achieve the desired individual or team results. However, while significant advancements have been made to better model and understand the dynamics of team interaction and its relationship (...) with task performance, appropriate measures of team coordination and computational methods to detect changes in coordination have not yet been widely investigated. Having the capacity to measure coordination in real time is quite promising as it provides the opportunity to provide adaptive feedback that may influence and regulate teams’ coordination patterns and, ultimately, drive effective team performance. A critical requirement to reach this potential is having the theoretical and empirical foundation from which to do so. Therefore, the first goal of the paper is to review approaches to coordination dynamics, identify current research gaps, and draw insights from other areas, such as social interaction, relationship science, and psychotherapy. The second goal is to collate extant work on feedback and advance ideas for adaptive feedback systems that have potential to influence coordination in a way that can enhance the effectiveness of team interactions. In addressing these two goals, this work lays the foundation as well as plans for the future of human-autonomy teams that augment team interactions using coordination-based measures. (shrink)