Home > Meeting Topics and Material > Weekly QUEST Discussion Topics, Sept 23

Weekly QUEST Discussion Topics, Sept 23

QUEST Discussion Topics and News Sept 23

QUEST Discussion Topics and News
Sept 23, 2011

1.) Continue the brainstorming session on the BURKA lab experiment and its potential use of their modeling / simulation environment as the sys2 cognition engine for a quest agent. This week we provided to some a homework assignment – redraw the conventional single / multi-sensor ATR diagrams using the concepts we’ve discussed in QUEST. We want to review the ideas of the audience on how we would propose to revolutionize one of our core missions (ATR – automatic target recognition). We will start by reviewing the current key ideas to improve ATR. Then we will discuss ideas on mapping those into our QUEST intuition / deliberative dual system formalism. Our hope is that this will lead to a specific set of ideas for the Burka lab researchers (for example how to improve tracking …).
2.) We’ve proposed one Burka lab experiment to investigate the application of QUEST concepts to solve the problem of what bits to exploit and at what resolution in a layered sensing environment. The idea is that we don’t have the option of processing all bits sensed for all possible meanings so we need an approach to decide what we look at and how we look at it. The best analogy is snail mail. When we go to the mail box we sort the material at different levels of resolution. Some things we discard by just looking at the envelope. Some we read the details of the source then discard. Some we actually have to open to discard. Some we have to read all the contents to decide how to process. The idea is to architect a multi-resolution Burka experiment where conflicts between the ‘simulation’ (sys2 representation) and the observations at coarse resolutions can drive exploitation resources and when those conflicts don’t exists (thus we can deliberate over our simulation versus gathering more detailed information from the sensor data) we can avoid expending those exploitation resources and potentially not drown in that data. We specifically want to add the details for ATRs and Trackers. We would also like to discuss the potential integration of human analysts in this discussion using technology to measure their sys1 response to a given set of data at a given resolution. We will examine the devices offered by the company Affectiva for this purpose.
3.) Affectiva: a continuation of our discussion – ‘can you make objective measurements of emotions or pain or even ‘redness’?’ – related to our cloud diagram that we were using as a homework assignment. Specifically accounting for relationships between external observables and aspects (both sys1 {subconscious} and sys2 {conscious}) of our internal representation of the world is our goal.
a. For example, when we say the word ‘red’ to describe some spectral aspect of some part of our visual sensory data that we’ve incorporated into our illusory cartesean theater what is the source of that articulated label and what is its relationship to the visual quale {the actual experience of what is seen} and to the sensory data {what is captured at the retina and encoded in pulses}.
b. We want to have the same discussion with respect to more complicated qualia like emotions and pain. We would like to account for the relationships between ‘frustration’ or ‘confusion’ to external observables like electro-dermal activity (EDA) and the internal qualia and also the internal sys1 states that we don’t have available to introspect over.
c. The focus of the discussion is to establish a position on how we can design an engineering experiment to allow quest agents to capture an accurate representation of the humans they are collaborating with in order to better estimate what context to provide that human to improve decision making.
4.) A recent article on impact of processing of scenes.
http://www.sciencenews.org/view/generic/id/334047/title/If_that%E2%80%99s_a_TV%2C_this_must_be_the_den

Specifically the impact of object recognition integrated within the context of the general outline of the scene information. The researchers presented to 28 people four scenes (bathroom, kitchen, intersection, and a playground). They then were presented objects associated with entities in those environments and the neural signatures for those objects representations were recorded (specifically in the lateral occipital cortex – LOC). The combination of the simple object representations was then compared to the scene presentation. The combination of the stove and the fridge responses matched the response to the kitchen. The implication is that within the LOC the representation of the scene is a simple combination of parts.
5.) Someday we will get to the other topic – the recent Sci Amer ‘Mind’ issue July 2011, a word doc with some snippets from some of the articles can be provided to stimulate discussion.

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