David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Minds and Machines 17 (1):11-25 (2007)
The broad range of capabilities exhibited by humans and animals is achieved through a large set of heterogeneous, tightly integrated cognitive mechanisms. To move artificial systems closer to such general-purpose intelligence we cannot avoid replicating some subset—quite possibly a substantial portion—of this large set. Progress in this direction requires that systems integration be taken more seriously as a fundamental research problem. In this paper I make the argument that intelligence must be studied holistically. I present key issues that must be addressed in the area of integration and propose solutions for speeding up rate of progress towards more powerful, integrated A.I. systems, including (a) tools for building large, complex architectures, (b) a design methodology for building realtime A.I. systems and (c) methods for facilitating code sharing at the community level
|Keywords||Holistic artificial intelligence Integration Large-scale architectures Scientific progress|
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