Zum Symposium "Sprache und Pragmatik" : 12.-16.5.86 in Lund

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Das schon traditionelle - fünfte - Lunder Symposium „Sprache und Pragmatik" war in diesem Jahr keinem pragmatischen Einzelproblem gewidmet. Vielmehr hatte Inger Rosengren zu einer Behandlung des Themas „Sprachsystem und Handlungssystem" geladen. Dies implizierte theoretische und methodologische Diskussionen sowie wissenschaftstheoretische Reflexion. Das komplexe Programm wurde durch das bewährte Konzept von Haupt- und Korreferaten abgewickelt; einige Einzelreferate kamen hinzu. Die Beiträge werden demnächst von Inger Rosengren bei Almqvist & Wiksell, Stockholm, herausgegeben

The Amendments that Mended America

After reading Eric Foner\u27s A Short History of Reconstruction, I began gathering sources about the Reconstruction amendments: the Thirteenth, Fourteenth, and Fifteenth. I collected sources that covered a large span of history and was able to construct my analysis of the Reconstruction amendments and how different interpretations changed throughout time

Infant and peer relationships in curriculum

The purpose of this thesis was to explore the relations between infants and their peers as they interacted intersubjectively with one another in an early childhood care and education environment and to investigate how the teacher was answerable through her engagement in these intersubjective events. Drawing upon a Bakhtinian methodological approach to research utterance was employed as my unit of analysis, providing a means to investigate the intersubjective interactions between infants and their peers in tandem with the teachers’ engagement in these interactions as answerable acts. This thesis builds on a previous pilot study which utilised dialogic methodology to investigate the nature of infant and teacher dialogue in an education and care context (White, Peter & Redder, 2015). The research that formed the basis for my subsequent analysis took place in a New Zealand education and care centre that catered for children less than two years of age. In the present study the same polyphonic video recording was used to capture infant and peer intersubjective interactions and the teacher’s engagement within these events. A mixed methods research approach was employed to qualitatively and quantitatively analyse the video data. The findings of this study suggest that infants are intersubjective agents in their relationships with peers and with teachers. Infants intentionally communicated with peers in lived relational experiences that were characterised by the fleeting, elongated or connected nature of their interactions. Mutual understanding, joint attention, attunement and the employment of synchronised language forms were features of infant ― peer intersubjective experiences. In addition, the findings revealed the capacity of infants and peers to relate with one another in social interactions that promote ‘dialogic spaces’ through which intersubjective relationships are sought. When teachers engaged in the infant ― peer intersubjective relations they either restrained by ‘shutting’ down or sustained by ‘opening up’ the intersubjective experience for the peers. The teacher’s body language was a feature of their engagement that contributed in a variety of ways to the infant ― peer intersubjective experience. Indeed how teachers engaged themselves in the interactions that were taking place between infants and their peers often determined the orientation of the teacher’s body positioning. The findings suggest when teachers restrained infant ― peer intersubjective dialogue, this form of engagement had the potential to alter how infants related to peers in subsequent interactions, highlighting the importance of sensitive, ‘in tune’ teacher engagement. Furthermore, the results highlight the pivotal role of the teacher as a ‘connecting’ feature within infant and peer intersubjective experiences, one who has the potential to ‘open up’ dialogic spaces for infants and their peer partners through engagement that is dialogic. These findings taken together may have implications for policymakers, educators and teacher education by ‘opening up’ dialogic spaces through which infants are seen as intersubjective agents and dialogic partners

TRADE-OFF ANALYSIS OF LARGE-SCALE SWARM ENGAGEMENTS

This research performs trade-off analysis on attacker-defender swarm engagements to compare the relative efficiency of factors governing swarm behavior, namely targeting algorithms and individual drone parameters. In particular, we examined algorithms developed for the Service Academies Swarm Challenge (SASC), a live-fly drone swarm exercise of swarm-on-swarm engagements. We performed this analysis with dynamic swarm simulations that permitted variations in swarm composition and behavior. This allowed us to confirm the qualitative results of swarm performance from the SASC. In addition, we used scaling analysis methods to perform quantitative trade-off analysis and developed functional forms to assess defender swarm fitness. Our results provide a framework for studying more complex swarm behaviors in follow-on research.Office of Naval Research/CRUSERLieutenant, United States NavyApproved for public release. Distribution is unlimited

Presence at history: Toward an expression of authentic historical content as game rules and play

This paper seeks to address the theme of the 2018 conference by examining the significant role game developers now have in mediating our understanding and engagement with history by placing players in historical events/scenarios thick with faithfully rendered artefacts, architecture, styles, and social encounters. In doing so, we argue for a new wave of historical games in which developers are no longer merely translating established scholarly perspectives on the past, but operating as historians through their practice-led research that attempts to bridge representational learning with more direct experience by historicizing the player’s experience, gameplay, and interactions. This paper principally illustrates its argument via a range of contemporary game titles that demonstrate a proclivity for creating authentic living socio-cultural systems, game mechanics, themes, and goals that invite players to learn about the past, distinct from games that employ uchronic times, alternate histories, or simply use history as window-dressing

3DPG: Distributed Deep Deterministic Policy Gradient Algorithms for Networked Multi-Agent Systems

We present Distributed Deep Deterministic Policy Gradient (3DPG), a multi-agent actor-critic (MAAC) algorithm for Markov games. Unlike previous MAAC algorithms, 3DPG is fully distributed during both training and deployment. 3DPG agents calculate local policy gradients based on the most recently available local data (states, actions) and local policies of other agents. During training, this information is exchanged using a potentially lossy and delaying communication network. The network therefore induces Age of Information (AoI) for data and policies. We prove the asymptotic convergence of 3DPG even in the presence of potentially unbounded Age of Information (AoI). This provides an important step towards practical online and distributed multi-agent learning since 3DPG does not assume information to be available deterministically. We analyze 3DPG in the presence of policy and data transfer under mild practical assumptions. Our analysis shows that 3DPG agents converge to a local Nash equilibrium of Markov games in terms of utility functions expressed as the expected value of the agents local approximate action-value functions (Q-functions). The expectations of the local Q-functions are with respect to limiting distributions over the global state-action space shaped by the agents' accumulated local experiences. Our results also shed light on the policies obtained by general MAAC algorithms. We show through a heuristic argument and numerical experiments that 3DPG improves convergence over previous MAAC algorithms that use old actions instead of old policies during training. Further, we show that 3DPG is robust to AoI; it learns competitive policies even with large AoI and low data availability