What kinds of social relationships can people have with computers? Are there activities that computers can engage in that actively draw people into relationships with them? What are the potential benefits to the people who participate in these human-computer relationships? To address these questions this work introduces a theory of Relational Agents, which are computational artifacts designed to build and maintain long-term, social-emotional relationships with their users. These can be purely software humanoid animated agents--as developed in this work--but they can also be non-humanoid or embodied in various physical forms, from robots, to pets, to jewelry, clothing, hand-helds, and other interactive devices. Central to the notion of relationship is that it is a persistent construct, spanning multiple interactions; thus, Relational Agents are explicitly designed to remember past history and manage future expectations in their interactions with users. Finally, relationships are fundamentally social and emotional, and detailed knowledge of human social psychology--with a particular emphasis on the role of affect--must be incorporated into these agents if they are to effectively leverage the mechanisms of human social cognition in order to build relationships in the most natural manner possible. People build

This is the manuscript that was published, with only minor copy-editing alterations, as: Haidt, J. (2001). The emotional dog and its rational tail: A social intuitionist approach to moral judgment. Psychological Review. 108, 814-834 Copyright 2001, American Psychological Association To obtain a reprint of the final type-set article, please go through your library’s journal services, or contact the author directly Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. Four reasons are given for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post-hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it de-emphasizes the private reasoning done by individuals, emphasizing instead the importance of social and cultural influences. The model is an intuitionist model in that it states that moral judgment is generally the result of quick, automatic evaluations (intuitions). The model is more consistent than rationalist models with recent findings in social, cultural, evolutionary, and biological psychology, as well as anthropology and primatology. Author notes

College students spend a significant amount of time using online social net- work services for messaging, sharing information, and keeping in touch with one another (e.g. [3, 10]). As these services represent a plentiful source of electronic data, they provide an opportunity to study dynamic

this paper we will show how the poverty of the stimulus available to language learners is the cause of linguistic structure, rather than a problem for it

Abstract—In this paper, we describe PEGASUS, an open source Peta Graph Mining library which performs typical graph mining tasks such as computing the diameter of the graph, computing the radius of each node and finding the connected components. As the size of graphs reaches several Giga-, Tera- or Peta-bytes, the necessity for such a library grows too. To the best of our knowledge, PEGASUS is the first such library, implemented on the top of the HADOOP platform, the open source version of MAPREDUCE. Many graph mining operations (PageRank, spectral clustering, diameter estimation, connected components etc.) are essentially a repeated matrix-vector multiplication. In this paper we describe a very important primitive for PEGASUS, called GIM-V (Generalized Iterated Matrix-Vector multiplication). GIM-V is highly optimized, achieving (a) good scale-up on the number of available machines (b) linear running time on the number of edges, and (c) more than 5 times faster performance over the non-optimized version of GIM-V. Our experiments ran on M45, one of the top 50 supercomputers in the world. We report our findings on several real graphs, including one of the largest publicly available Web Graphs, thanks to Yahoo!, with ≈ 6,7 billion edges. Keywords-PEGASUS; graph mining; hadoop I.

Human-human dialogue does not just comprise statements about the task at hand, about the joint and separate goals of the interlocutors, and about their plans. In human-human conversation participants often engage in talk that, on the surface, does not seem to move the dialogue forward at all. However, this talk -- about the weather, current events, and many other topics without significant overt relationship to the task at hand -- may, in fact, be essential to how humans obtain information about one another's goals and plans and decide whether collaborative work is worth engaging in at all. For example, realtors use small talk to gather information to form stereotypes (a collection of frequently co-occurring characteristics) of their clients -- people who drive minivans are more likely to have children, and therefore to be searching for larger homes in neighbourhoods with good schools. Realtors---and salespeople in general---also use small talk to increase intimacy with

We propose that humans are adapted to transfer knowledge to, and receive knowledge from, conspecifics by teaching. This adaptation, which we call 'pedagogy', involves the emergence of a special communication system that does not presuppose either language or high-level theory of mind, but could itself provide a basis facilitating the development of these human-specific abilities both in phylogenetic and ontogenetic terms. We speculate that tool manufacturing and mediated tool use made the evolution of such a new social learning mechanism necessary. However, the main body of evidence supporting this hypothesis comes from developmental psychology. We argue that many central phenomena of human infant social cognition that may seem puzzling in the light of their standard functional explanation can be more coherently and plausibly interpreted as reflecting the adaptations to receive knowledge from social partners through teaching.

People engage in small talk and conversational storytelling to provide information in engaging ways and to serve interpersonal goals such as building rapport and credibility. Embodied conversational interface agents, that represent the computer in its interaction with human users by way of a graphical humanoid body on a screen, can also profitably engage in these behaviors. We describe the ongoing development of an embodied conversational interface agent that is capable of multimodal input understanding and output generation and operates in a limited application domain in which both social and task-oriented dialogue are important. We discuss our plans for adding small talk and conversational storytelling capabilities to the system, and the unique requirements these phenomena place on the understanding, discourse planning, and generation components of a real-time conversational interface. Introduction Interlocutors typically have multiple goals in conversation (Tracy and Coupland 1991)...

In this research the authors examined whether conversational dynamics occurring within the first 5 minutes of a negotiation can predict negotiated outcomes. In a simulated employment negotiation, microcoding conducted by a computer showed that activity level, conversational engagement, prosodic emphasis, and vocal mirroring predicted 30 % of the variance in individual outcomes. The conversational dynamics associated with success among high-status parties were different from those associated with success among low-status parties. Results are interpreted in light of theory and research exploring the predictive power of “thin slices” of behavior (N. Ambady & R. Rosenthal, 1992). Implications include the development of new technology to diagnose and improve negotiation processes.

Abstract Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop’s eight speakers, plus a section designed to reflect the debates that took place during the workshop’s discussion sessions. The major theme that emerged during these sessions was the