Artificial Intelligence: A Modern Myth |
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Page 30
... semantics for the representation . This has not always been the case . Dimensions . It is important to have a clear ... semantic networks and frames , is still a major issue for theorists . ( Rothwell 1988 pp.23-24 ) 2.4.2 Problem ...
... semantics for the representation . This has not always been the case . Dimensions . It is important to have a clear ... semantic networks and frames , is still a major issue for theorists . ( Rothwell 1988 pp.23-24 ) 2.4.2 Problem ...
Page 178
... semantics , the impression may be given that semantics deals with meaning for the machine . But it would be a mistake to interpret this as corresponding in any serious sense to meaning as understood by humans . In fact , it has to be ...
... semantics , the impression may be given that semantics deals with meaning for the machine . But it would be a mistake to interpret this as corresponding in any serious sense to meaning as understood by humans . In fact , it has to be ...
Page 203
... semantic through and through : There are , to be sure , times when Connectionists appear to vacillate between ... semantics of representations at the " conceptual level " . ( Fodor & Pylyshyn 1987 p.5 ) Cussins alleges that the ...
... semantic through and through : There are , to be sure , times when Connectionists appear to vacillate between ... semantics of representations at the " conceptual level " . ( Fodor & Pylyshyn 1987 p.5 ) Cussins alleges that the ...
Contents
What is Artificial Intelligence? | 11 |
The Nature of Intelligence | 35 |
What is a Machine? | 75 |
Copyright | |
6 other sections not shown
Common terms and phrases
ability activity algorithmic analysis anthropomorphic approach argued artefacts articulation Artificial Intelligence assumptions attempt attributes belief Boden brain characteristics chess Chinese Room Cognitive Science coherence complex computer system concept connectionism connectionist construction context DENDRAL Dennett domain Dreyfus emerge emotion example existential existential fallacy expectations experience expert systems explicit explore expression fallacy Feigenbaum Fodor formal formalisation framework function fundamental heuristics human intelligence Ibid ineffable intellectual intelligence in machines intentional stance intentional system intentionality interaction with reality interpretation knowledge knowledge representation learning limits logic machine intelligence machine learning manipulation mathematical meaning mechanical mental metaphor mind Minsky natural language networks neural Newell notion object ontology perceptrons performance perhaps phenomena physical physical symbol system possible present problem psychological question rationality reasoning representation rules scientific semantics sense Simon simply solving strong AI structure symbol theory thinking traditional Turing test understanding words