Learning Objectives
Define the major image schemas (CONTAINER, PATH, FORCE, BALANCE, LINK, CENTER-PERIPHERY)
Trace how image schemas get metaphorically extended into abstract conceptual and linguistic domains
Locate image schemas embedded in LLM representations, attention patterns, and behavioral outputs
Apply image schema analysis to spatial AI reasoning systems and robotic language grounding
The pre-conceptual spatial patterns that form the deep skeleton of human conceptual structure.
This lesson builds on the theoretical foundations established earlier in the module and extends your understanding of how cognitive-linguistic principles apply directly to modern AI systems.
Learning Objectives
Define the major image schemas (CONTAINER, PATH, FORCE, BALANCE, LINK, CENTER-PERIPHERY)
Trace how image schemas get metaphorically extended into abstract conceptual and linguistic domains
Locate image schemas embedded in LLM representations, attention patterns, and behavioral outputs
Apply image schema analysis to spatial AI reasoning systems and robotic language grounding
Key Concepts
Define the major image schemas (CONTAINER, PATH, FORCE, BALANCE, LINK, CENTER-PERIPHERY)
Trace how image schemas get metaphorically extended into abstract conceptual and linguistic domains
Locate image schemas embedded in LLM representations, attention patterns, and behavioral outputs
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