Home > Meeting Topics and Material > QUEST Discussion Topics, 10/29

QUEST Discussion Topics, 10/29

QUEST Discussion Topics, 10/29

1.)  The initial discussion topic for this week will cover Capt Amerika’s talk on Flexible Autonomy (see notes below)

2.) With any remaining time, we will move on to a presentation on designing ‘conscious’ systems and what we envision a QUEST solution to look like.


Quest for Flexible Autonomy  Summary Notes:

Oct 2010

Capt Amerika

Issue:  Swimming in sensors – drowning in data (myth of ‘unmanned’ ISR – layered sensing, cyberspace has a human dimension, Integrated systems health monitoring, medical, …)

Current issue: myth of coming of intelligent machines/autonomy (resulting from great advances in processing throughput) all are based on the assumption that some miraculous solution to concept encoding (abstracting from pixels to information for example) will appear out of maturation of currently known machine intelligence approaches.  In all of these areas we are swimming in sensors and drowning in data.

Premise of this talk:  missing fundamental science (and math) for integrating multiple agents (some human some machine) will be required to solve these wicked (continually changing requirements) problems.   The second aspect of the proposed solution is that concepts are only definable in context (situations are the fundamental unit of cognition).  Situations can only be extracted from the environment with a closing of the loop around the sensor (query to sensing, proposed hypothesis situation, to new query – requires interaction).

Major points of talk:

1.)  RPA – CAP requires ~160 people, in space turning around a re-useable spacecraft takes 1.2k people and takes months (need to get to couple hundred and reduce turnaround to days), cyber Host based security services data is routinely discarded after recording due to the mismatch on PED capacity.

2.)  Integrated human machine solutions required – integration requires an ability of the human to ‘gist’ what the computer is doing / why it is doing it / and what it will do next – as well as the computer agents having a representation that answers these same questions about the human – requires a common framework.

3.)  Common framework – generalized agent definition (information processor – with precise definition of data, information, knowledge that is agent specific), extension of that formulation to definition of quest agents (incorporates what is known about human information processing) to include Theory of Mind (ability of humans to represent other human’s representation of the stimuli – thus the ability to predict the other agents ability).

4.)  Concepts in quest agents have a level of the representation that include a subjective (situation based) aspect.  ‘red is a concept not a wavelength nor a range of wavelengths’.

5.)  There exists a common set of math to describe the combined human – machine system of systems.

6.)  The ultimate goal of the common math is to predict and bound performance and allow decisions on investment in sensing, algorithmics or people to solve a given mission requirement.

 

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