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Course Outline
Introduction to AGI and Cognitive Architectures
- Defining AGI: The trajectory of artificial general intelligence
- Overview of cognitive architectures and their function in AGI
- Core concepts and foundational theories in cognitive science
Core Cognitive Architectures
- ACT-R: Architecture for Cognition and Learning
- Soar: Cognitive Architecture for Problem Solving
- CLARION: Cognitive Architecture for Action and Reflection
Integration of Cognitive Models in AGI Systems
- The impact of cognitive processes on machine learning
- Memory systems, decision-making, and attention mechanisms in AGI
- Developing scalable and adaptable cognitive systems for government operations
Building and Evaluating AGI Architectures
- Designing and simulating cognitive architectures
- Assessing the performance and accuracy of AGI models
- Validating AGI systems in operational environments
Applications of AGI and Cognitive Architectures
- Natural language processing and AGI models
- Robotics and cognitive agents
- Autonomous decision-making systems
Challenges and Future of AGI Development
- Ethical frameworks in AGI research
- The trajectory of cognitive architectures in advanced AI
- Emerging trends and innovations in AGI systems for government sectors
Summary and Next Steps
- Key strategic takeaways from the curriculum
- Resources for continued professional development
- Q&A and closing remarks
Requirements
- Comprehensive knowledge of artificial intelligence and machine learning
- Practical experience in cognitive modeling and computational systems
- Proficiency in neural networks and deep learning
Target Audience
- Cognitive scientists
- AI researchers
- AI system developers
14 Hours
Testimonials (2)
The historical knowledge of what when and why happened. The training helped me "connect the dots".
Jadwiga Marciniak - GE Aerospace Poland Sp. z o.o.
Course - Praktyczne wprowadzenie do AI w biznesie
Comparison between GenAI and friendly condition in class