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Cognitive Science 2: The Discipline Matures- Three Milestones


Language and micro-worlds

Language plays a central role in nearly all human intellectual endeavors, which makes it a good candidate for study by cognitive science.

In order to study hour we use language, some attempt to model natural language use. ELIZA is an early attempt, which simply performs certain outputs depending on inputs. It cannot report on it’s experiences, or show any changes based on the input. SHRDLU was an attempt to create a program that could use language to report on its environment. SHRDLU showed how knowledge could be built, represented, and integrated with pre-existing knowledge. It also showed how multiple processing components could work together on the information to create a meaningful output (cross-talk). It was a first step in showing language processing is algorithmic.

SHRDLU is definitely limited, and doesn’t represent how humans use language, but it is a step in the right direction. It is an example of how an algorithm can model the act of “understanding.”

How do mental images represent?

Different ways of mental representation are possible, and clever experiments help figure out which ones reflect how the mind works. 3-D figure manipulation experiments provide evidence for an “imagistic”representation in the mind as opposed to a digital.

An interdisciplinary model of vision

Many different levels of explanation exist in cognitive science, and vision is an example of a successful integration of many different explanatory disciplines.

Marr’s Vision (1982) was an early integration of multiple disciplines to explain vision. The topmost is the computational level, which is a very general explanation of what the task is, and how the process accomplishes it. The algorithmic level shows what instructions are performed on the information in order to create the output. The implementational level is the actual physical process that constitutes the other process.

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