Master the BDI architecture pattern that models rational agent behavior through beliefs, desires, and intentions—a bridge between philosophy and practical AI systems.
Master the mathematical and practical foundations of vector embeddings—the technology that enables AI agents to remember, search, and reason over vast knowledge bases.
Explore how the blackboard pattern enables multiple specialized agents to work together on complex problems through shared knowledge spaces and opportunistic reasoning.
Discover how Goal-Oriented Action Planning (GOAP) enables AI agents to dynamically create flexible plans that adapt to changing conditions, from game NPCs to modern autonomous systems.
