Joscha Bach Nick Cassimatis Ken Forbus Ben Goertzel Stacey Marsella John Laird Pat Langley Christian Lebiere Paul Rosenbloom Matthias Scheutz Satinder.

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Presentation transcript:

Joscha Bach Nick Cassimatis Ken Forbus Ben Goertzel Stacey Marsella John Laird Pat Langley Christian Lebiere Paul Rosenbloom Matthias Scheutz Satinder Singh Bob Wray Paul Bello Bob Marinier 1

Encourage cumulative research in AGI Encourage more formal evaluation and comparison Get people working on similar problems –Common testbeds, … –Will naturally lead to more collaboration, more cumulative research 2

1.Some capability (or set of capabilities) is required to achieve AGI –Symbol system hypothesis – Newell & Simon 2.Some capability (or set of capabilities) is sufficient to achieve AGI (or some piece of AGI) 3.A modification of a system or capability leads to improved performance. 3

How can we test claims across broad ranges of domains and tasks? Usually interested in broad competence not optimality? AGI must also have generality within a task –Play chess, explain own play, discuss strategy and tactics, teach chess, provide commentary, develop variations 4

Which component is responsible for behavior? –Fixed architecture Individual components? Structure of connectivity Shared representations? –Initial knowledge Is behavior result of clever knowledge engineering? –Learned knowledge Difficult to control Leads to lesion studies 5

1.Pursue specific questions –Often custom environment to stress one aspect of intelligence –Or more complex environment to explore combinations of environments 2.Compare to other research –Prior research in my group –Other related research in the field –Usually simple specialized environment 3.Evaluate generality –Implement on a wide variety of tasks - existing tasks that are available –Not developed by us – some ecological validity 4.Explore new (possibly large and complex) environment –Forced integration of many capabilities –We know it will stress system in new ways: might discover missing pieces –Does not lend itself to careful experimentation and credit assignment

Knowledge-rich – many tasks, complex environment 1.Large and complex skill knowledge 2.Large and complex conceptual knowledge [-embodied] Knowledge-lean – many tasks, complex environment 3.Structured training 4.Unstructured training 5.Single task which requires many different cognitive capabilities 1, 3, 4, and maybe 5 can probably share a similar environment 7

Develop concrete proposals how each approach and associated testbeds and tasks. Pursue funding to get testbeds developed. –Open Source 8