Machine learning of natural language
We met because we both share the same views of language. Language is a living organism, produced by neural mechanisms relating in large numbers as a society. Language exists between minds, as a way of communicating between them, not as an autonomous process. The logical 'rules' seem to us an epiphe nomena ·of the neural mechanism, rather than an essential component in language. This view of language has been advocated by an increasing number of workers, as the view that language is simply a collection of logical rules has had less and less success. People like Yorick Wilks have been able to show in paper after paper that almost any rule which can be devised can be shown to have exceptions. The meaning does not lie in the rules. David Powers is a teacher of computer science. Christopher Turk, like many workers who have come into the field of AI (Artificial Intelligence) was originally trained in literature. He moved into linguistics, and then into computational linguistics. In 1983 he took a sabbatical in Roger Shank's AI project in the Computer Science Department at Yale University. Like an earlier visitor to the project, John Searle from California, Christopher Turk was increasingly uneasy at the view of language which was used at Yale
x, 358 pages ; 25 cm
9780387195575, 9783540195573, 0387195572, 3540195572
20263032
1 Art, Science and Engineering
Cognitive Structures
Scientific Method
Language is Contrastive
2 Metaphor as a Cognitive Process
Conjecture and Refutation, Theories and Hypotheses
Specialization and Abstraction, Induction and Generalization
Partial Analysis and Noise
The Importance of Errors and Restrictions
3 Psychology and Psycholinguistics
The Observable Processes of Acquisition
External Influences: Parents, Imitation, and Correction
Expansion and Reduction
4 Language Defects and Correction
Rate and Order of Learning
Telegraphic Speech
Parents and Teachers: Good and Bad Examples
Reinforcement: Punishment and Reward
5 Cognition and Restriction
The Cognitive Processes of Language Acquisition
The Magical Number Seven
Memory and Capacity Phenomena
Adult Characteristics
6 Nativism and Constructivism
Representations: Deep Structure and Language Acquisition
Acquisition Models, Chomsky and Piaget
Computer Programs as Psychological Models
7 Neurology and Neurolinguistics
Neuroanatomy: Brains, Neurons, and Synapses
Neurophysiology and the Effects of Plasticity
Neural Communication and Languages of the Brain
Neural Nets: Connectionistic and Locationistic Models
8 The Nature of Language
The Quintessence of Language
Epistemology, Phonology, and Prosody
Culture, Perspectives, and Metaphor
9 The Mechanics of Language
Contrast and Similarity: Paradigmatic Learning and Context
The Structures of Language
Models of Grammar
10 The Ubiquity of the Sentence
Pronouns and Anaphora
Recursion of Syntax and Parsing
Transformational Grammar
Generative Grammar
Learning Process and Idiolect
11 Computer Science and Artificial Intelligence
Pattern Recognition, Problem Solving and Heuristic Search
Learning Strategies
Problems and Theoretical Limitations
12 Heuristics and Analytic Intransigence
Automata and Formal Languages
Methodologies: Implementation vs Experimentation
Cybernetics and Robotics
Deletionless Strategies
Formalisms
Clauses: Horn and non-Horn, unit and non-unit Systems: LUSH and PROLOG
13 Postulates, Claims and Hypotheses
The Bases of Meaning and Learning
The Organization of Concepts in Learning
The Process of Learning
The Artificial Subsumes the Natural
14 Computer Modelling Experiments
Batteries One to Seven
A Generalized Toy World Package
Partial Analysis of NLA
Future Systems
Conclusions