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Cognitive Design for Artificial Minds
Acknowledgements
Cognitive science and artificial intelligence: death and rebirth of a collaboration
When Cognitive Science was AI
From the general problem-solver to the society of mind: cognitivist insights from the early AI era
Heuristics and AI eras
Modelling paradigms and AI eras: cognitivist and emergentist perspectives
Death and rebirth of a collaboration
Cognitive and machine-oriented approaches to intelligence in artificial systems
Nature- vs. machine-inspired approaches to artificial systems
Functionalist vs. structuralist design approaches
Levels of analysis of computational systems
The space of cognitive systems
Functional and structural neural systems
Functional and structural symbolic systems
Principles of the cognitive design approach
Classical, bounded, and bounded-rational models of cognition
Resource-rationality models
Kinds of explanations
Levels of plausibility and the minimal cognitive grid (MCG)
Examples of cognitively inspired systems and application of the Minimal Cognitive Grid
Modern AI systems: cognitive computing?
Cognitive architectures
SOAR
ACT-R
Two problems for the knowledge level in cognitive architectures
Knowledge size and knowledge heterogeneity in SOAR and ACT-R
DUAL PECCS
Evaluating the performances of artificial systems
“Thinking” machines and Turing Test(s)
The Chinese Room
The Newell test for a theory of cognition
The Winograd Schema Challenge
DARPA challenges, RoboCup, and RoboCup@Home
Comparison
The next steps
The road travelled
The way forward
Towards a standard model of mind/common model of cognition
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