Stillings, N. A., Chase, C. H., Weisler, S. E., Feinstein, M. H., Garfield, J. L., & Rissland, E. L. (1995). Cognitive Science: An Introduction. MIT Press.
Summary
Information processes are formal, goal-oriented operations with symbols related to information in the world. Understanding information processes requires analysis at the knowledge, formal, and physical levels.
Key terms
- Cognitive = perceiving and knowing; cognitive science is the science of mind
- Semantic = a quality that describes meaningful information (e.g. having context or significance); also known as intentional qualities
- Semantic mapping = connects the representation to the domain
- Semantic analysis = concerned with a system’s enviornmental structure, information access, and accomplishment of goals through deploying information; also known as competence theory or knowledge-level analysis
- Representation = allows information to be used for a computation; also known as symbol
- Representational mapping = connects knowledge and formal levels of analysis
- Syntax = rules of symbol construction; representational schemes that allow new symbols to be constructed from simpler ones are called combinatorial, generative, or productive
- Semantic interpretation = meaning of a complex symbol constructed from its “syntatic parts”; representational schemes where interpreting complex structures is determined by interpreting their parts have a compositional semantics
- Algorithm = a formal procedure or information process that operates on a representation; algorithms analyze the syntatic structures of symbolic inputs and build syntactically structured outputs
- Implementational mapping = connects formal and physical levels of analysis
Reading notes
Fundamental concepts of cognitive science
Information processes are contentful and purposeful
- Information processes allow a system to make a goal-oriented, systemic response to a change in environmental conditions
- An information processing system must competently employ information
- The process must use representation
- Semantic (knowledge-based) analyses are concerned with people’s awareness of their goals and ability to use information to pursue them
Information processes are representational
- Understanding how information is represented for a computation is necessary for understanding how the computation is performed
- Representations have syntactical rules that allow complex symbols to be constructed from simple ones in a generative way
- The complex symbol can be understood from the meaning of its syntatic parts
- Algorithms can be defined by the syntactic structures of their inputs and outputs
- Algorithms represent a function correctly by maintaining the representational mapping between symbols and literal information
Information processes can be described formally
- Algorithms are formal procedures that manipulate patterns in their representation, rather than acting on a real domain
- Algorithms can be performed by physical systems (biological or engineered) without higher knowledge of their meanings, because the algorithmic process is only indirectly meaningful (through semantic mapping)
- Cognitive science distinguishes between formal operations on symbols and how symbols are related to what they stand for
Levels of information processes
Knowledge
- Knowledge-level analysis, which includes understanding representational mapping, is concerned with the algorithm’s function
- Knowledge-level analysis reveals to general principles about a system’s significance or purpose
Formal
- Formal information processes underlie (i.e. lower level) the competency and knowledge expressed through visible behavior
- Formal-level analysis is needed to distinguish between systems that have different algorithms but the same semantics
Physical
- Information processes can only occur when physically implemented
- The ability of a system to carry out its formal information processes depends on its physical construction or instantiation