Track 1: Cognitive Architectures and AI
Integration of cognitive models into AI systemsHybrid AI models: Rule-based and data-driven approaches
Memory and learning mechanisms in cognitive architectures
Track 2: Machine Learning and Cognitive Science
Machine learning algorithms inspired by human learning processesExplainability and transparency in AI models
Deep learning for human-like decision-making
Track 3: Human-AI Interaction and Cognitive Modeling
Human-computer interaction and cognitive modelingImpact of AI systems on human cognition
AI-assisted learning and education systems
Track 4: Neuroscience-Inspired AI
AI models inspired by neuroscienceBrain-computer interfaces and cognitive AI
Modeling attention, perception, and consciousness
Track 5: Natural Language Processing and Cognitive Models
Cognitive approaches to language understanding and generationHuman-like cognitive processes in language models
AI in speech and emotional analysis
Track 6: Ethics and Cognitive AI
Ethical considerations in cognitive modelsLimits of AI and human cognition
Bias and ethical consequences in AI decision-making
Track 7: Cognitive Robotics and Autonomous Systems
Cognitive modeling in roboticsHuman-like problem-solving abilities
Cognitive decision-making in autonomous systems
Track 8: Decision-Making and Problem-Solving
Heuristics and biases in human and artificial decision-makingAI systems for complex problem-solving
Explainable AI (XAI) for transparent decision-making
Track 9: Emotion, Affect, and Social Cognition
Affective computing and emotion recognitionAI systems for understanding and simulating emotions
Cognitive models of empathy and social interaction
Track 10: Applications of Cognitive AI
AI in healthcare: cognitive models for diagnosis and treatmentAI in education: personalized learning systems
Cognitive models for autonomous systems (e.g., self-driving cars)
Track 11: Evaluation and Benchmarking of Cognitive Models
Metrics for evaluating cognitive modelsBenchmark datasets for cognitive AI research
Validation of cognitive models through empirical studies
Track 12: Emerging Trends and Future Directions
Quantum computing and cognitive modelsCognitive models for general artificial intelligence (AGI)
Interdisciplinary approaches to advancing cognitive AI