Symbol Grounding is a fundamental challenge in AI research that concerns the ability of machines to connect their symbolic representations to real-world referents and acquire meaningful understanding from their interactions with the environment. In other words, it deals with how machines can understand and represent the meaning of objects, concepts, and events in the world. Without the ability to ground symbolic representations in the real world, machines cannot acquire the rich and complex meanings necessary for intelligent behavior, such as language processing, image recognition, and decision-making.

Related Pages: Truth, Semantics, & Meaning, Philosophy of Language