Information and mechanical models of intelligence
What can we learn from cognitive science
Bibliographic Data
| ID | 20484252 |
|---|---|
| Authors | Maria Eunice Quilici Gonzalez (0000-0002-3837-4644, Universidade Estadual Paulista (UNESP), Marília, Brazil, corresponding author) |
| Year | 2005 |
| Volume | 13 |
| Issue | 3 |
| Pages | 565-582 |
| Publication date | 2005-12-20 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Pragmatics & Cognition (JOURNAL) |
| Journal identifiers | ISSN: 0929-0907 • E-ISSN: 1569-9943 |
| Publisher | John Benjamins Publishing Company (PUBLISHER • NL) |
| DOI | 10.1075/pc.13.3.09qui |
| OpenAlex | W2093792735 |
| Language | EN |
The impact of new advanced technology on issues that concern meaningful information and its relation to studies of intelligence constitutes the main topic of the present paper. The advantages, disadvantages and implications of the synthetic methodology developed by cognitive scientists, according to which mechanical models of the mind, such as computer simulations or self-organizing robots, may provide good explanatory tools to investigate cognition, are discussed. A difficulty with this methodology is pointed out, namely the use of meaningless information to explain intelligent behavior that incorporates meaningful information. In this context, it is inquired what are the contributions of cognitive science to contemporary studies of intelligent behavior and how technology may play a role in the analysis of the relationships established by organisms in their natural and social environments
Cognition · Cognitive science · Data science · Knowledge management · Management science · Social intelligence · Cognitive Science and Education Research · Cognitive Science and Mapping · Computability, Logic, AI Algorithms · Computer Science · Engineering · Psychology · Social Psychology · Artificial Intelligence
| Highly cited | No |
|---|