The Foundations of Artificial Intelligence: A Sourcebook
Derek Partridge, Yorick Wilks
Cambridge University Press, Apr 26, 1990 - Computers - 498 pages
This outstanding collection is designed to address the fundamental issues and principles underlying the task of Artificial Intelligence.
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What is AI anyway?
What kind of information processing is intelligence?
The formal foundations of AI
a new perspective
Prolegomena to a theory of mechanized formal reasoning
Levels of theory
AI a personal view
theories programs and rational reconstructions
a case study in AI methodology
Is AI special in regard to its methodology?
Is there anything special about AI?
What sort of a thing is an AI experiment?
We need better standards for AI research
Does connectionism provide a new paradigm for AI?
Why there STILL has to be a language of thought
Has AI helped psychology?
Whats in an AI program?
Programs and theories
models and theories
The nature of AI principles
Artificial methodology meets philosophy
The role of representations
Can there be? Are we?
Evolution error and intentionality
The role of programs in AI
What kind of field is AI?
the mistaken foundations of AI
Rational reconstruction as an AI methodology
Connectionism and the foundations of AI
Some comments on Smolensky and Fodor
Representation and highspeed computation in neural networks
The role of correctness in AI
Does AI have a methodology different from software engineering?
AI computer science and education
Limitations on current AI technology
The challenge of open systems
Towards a reconciliation of phenomenology and AI
The superarticulacy phenomenon in the context of software manufacture
Annotated bibliography on the foundations of AI
Other editions - View all
abstract algorithms analysis applied architecture argue argument artificial intelligence Aunty autoepistemic logic behavior brain Bundy chess claim closed world assumption cognitive cognitive science complex computer science concept connectionism connectionist defined described discussion domain Dretske Dreyfus engineering evaluation example expert systems explain fact first-order logic Fodor formal function goal heuristic human hypothesis implementation important inference information processing input interaction interpretation intuitive kind knowledge learning Lenat linguistic logic programming machine mathematics meaning mechanism mental metatheory methodology natural language natural-language neural Newell non-monotonic reasoning objects operations output paper particular perfect model semantics performance phenomena physical physical symbol system position possible predicate principles problem procedures proposed psychology question relevant representation role rules scientific semantics of logic sense sentences simple Smolensky solve space specific SPIV symbolic paradigm task techniques theoretical theory thought two-bitser understanding