Aligned with
This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.
This track focuses on the application of computational cognitive models to understand health-related behaviors and decision-making processes. It aims to explore how these models can enhance our understanding of patient cognition and treatment adherence.
This session will delve into the intersection of computational cognitive neuroscience and psychological processes. Researchers are invited to present studies that utilize computational methods to investigate neural mechanisms underlying cognition.
This track emphasizes the computational modeling of perception and memory systems. Contributions should address how these models can inform our understanding of cognitive functions and their implications for health.
This session will examine cognitive models related to decision-making in interactive human-machine systems. It seeks to highlight approaches that enhance collaborative decision support through computational methods.
This track focuses on cognitive models that facilitate situation awareness in dynamic environments. Papers should explore the role of computational modeling in understanding how individuals and machines perceive and respond to situational contexts.
This session invites contributions that investigate the relationship between language processing and cognitive functions through computational linguistics. The aim is to understand how language influences cognition and decision-making.
This track will address the evaluation metrics and performance assessment of hybrid human-machine systems. Researchers are encouraged to present methodologies for measuring effectiveness in collaborative environments.
This session will explore computational approaches to spatial and temporal reasoning within cognitive models. The focus will be on how these models can enhance understanding of goal-directed behavior and intention.
This track emphasizes the role of ontology-based computing in advancing computational cognitive science. Contributions should discuss how ontological frameworks can improve data integration and knowledge representation.
This session will focus on the development and evaluation of collaborative decision support systems. Papers should highlight innovative computational approaches that facilitate teamwork between human and machine agents.
This track will explore the acquisition, construction, and adaptation of computational models in cognitive science. Researchers are invited to present findings on how adaptive learning can enhance model performance in real-world applications.