Hasil untuk "Information theory"

J. Sweller, Paul Ayres, Slava Kalyuga

J. Hespanha

Joao P. Hespanha February 4, 2015 Comments and information about typos are very welcome. Please contact the author at hespanha@ece.ucsb.edu. Errata 1) In page 7, the MATLAB R © command should read sys_ss=ss(A,B,C,D,... ’InputName’, {’input1’, ’input2’,...},... ’OutputName’,{’output1’,’output2’,...},... ’StateName’, {’state1’, ’state2’,...}); 2) In page 15 in Figure 2.3, the angle θ2 is incorrectly drawn, it should be drawn as follows:

E. Koechlin, C. Summerfield

T. Copeland, D. Galai

Daniel F. Gruhl, David Liben-Nowell, R. Guha et al.

D. Walker, F. Myrick

M. Yi, J. Jackson, Jae S. Park et al.

R. Hambleton, H. Swaminathan

J. Bogdanoff

W. Cleveland, R. McGill

D. Avison, M. D. Myers

L. Valiant

D. Westerman, P. Spence, B. V. D. Heide

M. Humphreys, W. Revelle

S. Snell

S. Balakrishnan, M. Koza

Anika Meyer, Marlene Holmner, Theo JD. Bothma

Introduction. The ‘Emergent Zone’ is a boundary space where humans and AI co-construct meaning, authorship, and responsibility in response to the transformative impact of conversational information retrieval systems. Method. Develop a conceptual framework by synthesising the information foraging theory, Vygotsky’s Zone of Proximal Development (ZPD), and Kuhlthau’s Zones of Intervention, all grounded in LIS literature and expanded through critical AI perspectives. Analysis. AI’s roles as forager, scaffolder, and intervener are illustrated by illustrative exemplum cases from library references, disinformation detection, and learning environments, revealing both efficiencies and profound challenges to agency and accountability. Results. The framework underscores the urgent need for new critical literacies (e.g., prompt, interpretive, algorithmic, and ethical) and positions meta-literacy as an integrative foundation for LIS. Conclusion. The Emergent Zone advances scholarship on AI–human interaction, calling for new literacies and reimagined pedagogies and ethics in LIS, and proposes future research emphasising justice-oriented and cross-cultural approaches.

Gerrit Schmid, Daniel A. Braun

Abstract Division of labor and specialization are common principles observed across all levels of biological organisms and societies, including humans that often rely on specialized roles to achieve a shared goal in complex coordination tasks. Understanding these principles in a quantitative fashion remains a challenge. In this study, we explore a novel experimental paradigm where two specialized groups of human players—a sensor group and an actor group—collaborate to accomplish a shared sensorimotor task of steering a cursor into a target. With all decision-makers initially unaware of their contribution and in the absence of verbal communication, the study explores how the group dynamics evolve over time, evaluating performance in terms of learning speed, group coherence and intergroup coordination. To gain quantitative insights, we simulate different computational models, including Bayesian learning and bounded rationality models, to describe human participants’ behavior. We also relate our findings to perceptual control theory, which emphasizes hierarchical control systems in which information flows bidirectionally between levels. Our results show that both human participants and model-based simulations (Bayesian and bounded rational agents) successfully complete the task. Over time, mutual information between actors and sensors increases, and cooperative behavior emerges within the groups. Interestingly, model-free hierarchical reinforcement learning fails to account for the observed data, being overwhelmed by task variability. In contrast, model-based approaches can be shown to generalize to larger groups and more complex network structures in evolutionary simulations. Our findings highlight the importance of internal models and concurrent co-optimization in facilitating adaptive coordination, offering insights into distributed information processing mechanisms.

Advaita S. Nigudkar, Jagruti R. Wandrekar

Background: Exploring factors that determine resilience in the Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual+ (LGBTQIA+) community as described in the minority stress model and developing interventions to promote individual and community resilience are emerging goals to facilitate LGBTQIA+ mental health. In this pilot study, researchers’ objectives were two-fold to build a participant-derived theory on resilience in the LGBTQIA+ community and to develop and evaluate the feasibility and usefulness of an intervention module to build resilience. Methods: Online group therapy sessions were conducted under the Sexuality, Awareness, Acceptance, Health, and Support (SAAHAS) framework, with queer mental health professionals as facilitators using a peer-cum-expert stance. Following a detailed intake and assessment using the Connor Davidson Resilience Scale, a group discussion on Understanding Resilience in the first session was used to identify resilience components. In the remaining 6 sessions, facilitators primarily used Queer Affirmative Cognitive Behavior Therapy techniques pertinent to these components to address challenges in the domains of self, family of origin, and intimate partner relationships. A feedback form was used after the final session to evaluate usefulness. Results: The 6 components identified as crucial to LGBTQIA+ resilience were building self-worth, stigma competence, cognitive coping, emotional coping, general social and interpersonal skills, and accessing information and resources. 27 participants from the LGBTQIA+ community attended at least one session. Participant feedback suggested that the participants believed that the group was a safe space, perceived an increase in their resilience after the intervention, reported improvement on all 6 resilience components, and believed that they had better skills to navigate challenges in the 3 settings of self, family, and intimate partner relationships. Conclusion: The SAAHAS intervention module can be a useful cost-effective framework to promote individual resilience, and the group therapy setting itself is a useful tangible community resilience resource.

Mutia Kardina, Aldri Frinaldi

The development of information and communication technology drives the transformation of public services towards a more efficient, transparent, and participatory digital direction. The Agam Regency Government responded to this change by presenting the SILETON (Integrated Online Electronic Service System) application as an innovation in population administration services. However, in the implementation process, various obstacles were still found, such as low digital literacy of the community, limited technological infrastructure, and uneven levels of service adoption. This study aims to analyze the process of innovation diffusion of the SILETON application based on Everett Rogers' Diffusion of Innovation theory, assess its contribution to the implementation of smart governance, and formulate strategies for optimizing digital-based services at the regional level. The method used in this study is a descriptive qualitative approach, with data collection techniques in the form of in-depth interviews, observation, and documentation. Informants were selected purposively involving the Agam Regency Population and Civil Registry Office, application managers, and user communities. The results of the study show that the SILETON innovation diffusion process has shown significant progress, but is not evenly distributed across all levels of society. This application contributes to increasing transparency, efficiency, and public participation as characteristics of smart governance. Suggested optimization strategies include increasing digital literacy, strengthening network infrastructure, developing user-friendly application features, and active collaboration between agencies. These findings emphasize the importance of a holistic approach in driving the success of digital innovation in local government to create more inclusive and adaptive public services.