Diversity and Communication in Teams: Improving Problem Solving or Creating Confusion?

Despite the rich and interdisciplinary debate on the role of diversity and communication in group problem solving, as well as the recognition of the interactions between the two issues, they have been rarely treated as a joint research topic. In this paper we offer a computational model of agents in teams and we assess the impact of various levels of diversity and communication on individual and collective performance at solving problems. By communication we intend a conversation on the persuasiveness of the features characterizing the problem setting. By diversity we mean differences in how agents build problem representations that allow them to access various solutions. We deploy the concept of diversity along two dimensions: knowledge amplitude, that is the relative amount of available knowledge with respect to the complete representation of a problem, and knowledge variety, that, for a given level of knowledge amplitude, regards differences in knowledge constituents Our results highlight the peculiar role and the interactions between the different sources of variety. Regarding knowledge amplitude, when agents have an incomplete representation of the problem, communication provides just confusion as it is difficult to find a common language for sharing thoughts, and agents perform better alone. Adding knowledge variety to this scenario, effects of communication are even more devastating. Conversely, as the representation of the problem gets more and more complete, communication becomes effective and displays a clear non-monotonic effect: after an optimal point, performance declines very rapidly and gets worse than the individual behavior. In this case, the introduction of knowledge variety further increases performance in teams, since benefits from integrating partial representations of the problem occur more frequently than communication clashes. Finally, highly diverse teams seem to be less sensitive to changes in communication strength, while as diversity declines, even small discrepancies from the optimal communication strength level might account for a strong variability of performance. In particular, overestimation of the required communication effort might cause severe performance breakdowns. Our results suggest that organizations and firms should jointly consider communication intensity and different sources of diversity in teams, since interactions among these variables might result in problem solving groups resembling more a Tower of Babel than an effective and helpful workplace.problem solving; diversity; heterogeneous agents; communication; constraint satisfaction; neural networks; causality

Diversity Communication in Teams: Improving Problem Solving or Creating Confusion?

Despite the rich and interdisciplinary debate on the role of diversity and communication in group problem solving, as well as the recognition of the interactions between the two topics, they have been rarely treated as a joint research issue. In this paper we develop a computational approach aimed at modeling problem solving agents and we assess the impact of various levels of diversity and communication in teams on agents' performance at solving problems. By communication we intend a conversation on the persuasiveness of the features characterizing the problem setting. By diversity we mean differences in how agents build problem representations that allow them to access various solutions. We deploy the concept of diversity along two dimensions: knowledge amplitude, that is, the amount of available knowledge (compared to the complete representation of a problem), and knowledge variety, which pertains to the differences in agents' knowledge endowments.x10Our results show the different impact of these two sources of variety on problem solving performance in teams, as well as their interplay. Regarding knowledge amplitude, when agents' representation of the problem is considerably incomplete, communication provides confusion as it is difficult to find a common language for sharing thoughts, and agents perform better alone. Adding knowledge variety to this scenario, the effects of communication are even more negative. Conversely, as the representation of the problem gets more and more complete, communication becomes more and more effective. Albeit displaying a clear non-monotonic effect: increasing the communication strength, performance increases until an optimal point, after which it declines and gets very rapidly worse than individual behavior. In this case, the introduction of knowledge variety further increases performance in teams, since benefits from integrating partial representations of the problem occur more frequently than communication clashes. Finally, highly diverse teams seem to be less sensitive to changes in communication strength, while as diversity declines, even small discrepancies from the optimal communication strength level might account for a strong variability of performance. In particular, overestimation of the required communication effort might cause severe performance breakdowns.x10Our results suggest that organizations and firms should jointly consider communication intensity and different sources of diversity in teams, since interactions among these variables might result in problem solving groups resembling more a Tower of Babel than an effective and helpful workplaceproblem solving; diversity; heterogeneous agents; communication; constraint; satisfaction; neural networks; causality

Learning non-monotonic Logic Programs to Reason about Actions and Change

[Resumen] El objetivo de esta tesis es el diseño de métodos de aprendizaje automático capaces de encontrar un modelo de un sistema dinámico que determina cómo las propiedades del sistema con afectadas por la ejecución de acciones, Esto permite obtener de manera automática el conocimiento específico del dominio necesario para las tareas de planficación o diagnóstico así como predecir el comportamiento futuro del sistema. La aproximación seguida difiere de las aproximaciones previas en dos aspectos. Primero, el uso de formalismos no monótonos para el razonamiento sobre acciones y el cambio con respecto a los clásicos operadores tipo STRIPS o aquellos basados en formalismos especializados en tareas muy concretas, y por otro lado el uso de métodos de aprendizaje de programas lógicos (Inductive Logic Programming). La combinación de estos dos campos permite obtener un marco declarativo para el aprendizaje, donde la especificación de las acciones y sus efectos es muy intuitiva y natural y que permite aprender teorías más expresivas que en anteriores aproximaciones

From Biological to Synthetic Neurorobotics Approaches to Understanding the Structure Essential to Consciousness (Part 3)

This third paper locates the synthetic neurorobotics research reviewed in the second paper in terms of themes introduced in the first paper. It begins with biological non-reductionism as understood by Searle. It emphasizes the role of synthetic neurorobotics studies in accessing the dynamic structure essential to consciousness with a focus on system criticality and self, develops a distinction between simulated and formal consciousness based on this emphasis, reviews Tani and colleagues' work in light of this distinction, and ends by forecasting the increasing importance of synthetic neurorobotics studies for cognitive science and philosophy of mind going forward, finally in regards to most- and myth-consciousness

Probabilistic Action Language pBC+

We present an ongoing research on a probabilistic extension of action language BC+. Just like BC+ is defined as a high-level notation of answer set programs for describing transition systems, the proposed language, which we call pBC+, is defined as a high-level notation of LP^{MLN} programs - a probabilistic extension of answer set programs. As preliminary results accomplished, we illustrate how probabilistic reasoning about transition systems, such as prediction, postdiction, and planning problems, as well as probabilistic diagnosis for dynamic domains, can be modeled in pBC+ and computed using an implementation of LP^{MLN}. For future work, we plan to develop a compiler that automatically translates pBC+ description into LP^{MLN} programs, as well as parameter learning in probabilistic action domains through LP^{MLN} weight learning. We will work on defining useful extensions of pBC+ to facilitate hypothetical/counterfactual reasoning. We will also find real-world applications, possibly in robotic domains, to empirically study the performance of this approach to probabilistic reasoning in action domains

Which side are you on? Insider-Outsider classification in conspiracy-theoretic social media

Social media is a breeding ground for threat narratives and related conspiracy theories. In these, an outside group threatens the integrity of an inside group, leading to the emergence of sharply defined group identities: Insiders -- agents with whom the authors identify and Outsiders -- agents who threaten the insiders. Inferring the members of these groups constitutes a challenging new NLP task: (i) Information is distributed over many poorly-constructed posts; (ii) Threats and threat agents are highly contextual, with the same post potentially having multiple agents assigned to membership in either group; (iii) An agent's identity is often implicit and transitive; and (iv) Phrases used to imply Outsider status often do not follow common negative sentiment patterns. To address these challenges, we define a novel Insider-Outsider classification task. Because we are not aware of any appropriate existing datasets or attendant models, we introduce a labeled dataset (CT5K) and design a model (NP2IO) to address this task. NP2IO leverages pretrained language modeling to classify Insiders and Outsiders. NP2IO is shown to be robust, generalizing to noun phrases not seen during training, and exceeding the performance of non-trivial baseline models by $20\%$.Comment: ACL 2022: 60th Annual Meeting of the Association for Computational Linguistics 8+4 pages, 6 figure

Naval Integration into Joint Data Strategies and Architectures in JADC2

NPS NRP Technical ReportAs Joint capabilities mature and shape into the Joint All Domain C2 Concept, Services, COCOMs and Coalition Partners will need to invest into efforts that would seamlessly integrate into Joint capabilities. The objective for the Navy is to study the options for Navy, including Naval Special Warfare Command under SOCOM, on how to integrate Navy's data strategy and architecture under the unifying JADC2 umbrella. The other objectives are to explore alternatives considered by the SOCOM and the Air Force, which are responsible for JADC2 Information Advantage and Digital Mission Command & Control. A major purpose of Joint, Services/COCOMs, agencies and Coalition Partners capabilities is to provide shared core of integrated canonical services for data, information, and knowledge with representations for vertical interoperability across all command levels and JADC2, lateral interoperability between Naval Service/COCOMs, and any combination of JADC2 constituents, agencies, and coalition partners. Our research plan is to explore available data strategy options by leveraging previous NRP work (NPS-20-N313-A). We will participate in emerging data strategy by Navy JADC2 project Overmatch. By working with MITRE our team will explore Air Force JADC2 data strategy implemented in ABMS DataOne component. Our goal is to find a seamless integration between Naval Data Strategy and data strategies behind JADC2 Information Advantage and Digital Mission Command & Control capabilities. Our plan includes studying Service-to-Service and Service-to-COCOM interoperability options required for Joint operations with a goal to minimize OODA's loop latency across sensing, situation discovery & monitoring, and knowledge understanding-for-planning, deciding, and acting. Our team realizes JADC2 requires virtual model allowing interoperability between subordinate C2 for services, agencies, and partner. Without such flexible 'joint' intersection organizational principal hierarchical structure it would be impossible to define necessary temporal and spatial fidelities for each level of organizational command required for implanting JADC2. Research deliverables will document the results of the exploration of Joint, COCOM, Agency and Partner Data Strategies approaches as JADC2 interoperability options to the emerging JADC2. We strive for standard JADC2 interface. Keywords: JADC2, ABMS, DataOne, Information Advantage, Digital Mission Command, IntegrationN2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Economic growth, innovation systems, and institutional change: a trilogy in five parts

Development and growth are products of the interplay and interaction among heterogeneous actors operating in specific institutional settings. There is a much alluded-to, but under-investigated, link between economic growth, innovation systems, and institutions. There is widespread agreement among most economists on the positive reinforcing link between innovation and growth. However, the importance of institutions as catalysts in this link has not been adequately examined. The concept of innovation systems has the potential to fill this gap. But these studies have not conducted in-depth institutional analyses or focussed on institutional transformation processes, thereby failing to link growth theory to the substantive institutional tradition in economics. In this paper we draw attention to the main shortcomings of orthodox and heterodox growth theories, some of which have been addressed by the more descriptive literature on innovation systems. Critical overviews of the literatures on growth and innovation systems are used as a foundation to propose a new perspective on the role of institutions and a framework for conducting institutional analysis using a multi-dimensional typology of institutions. The framework is then applied to cases of Taiwan and South Korea to highlight the instrumental role played by institutions in facilitating and curtailing economic development and growth