Weekly QuEST Discussion Topics and News, 19 Sept

September 19, 2014 Leave a comment

QuEST 19 Sept 2014:

1.) We want to start making a few remaining comments we didn’t get to last week – the discussion was prompted by our colleague Qing W from Rome on Semantic Web efforts and specifically how they relate to ‘big-data’ and how they both relate to QuEST. Recall our Rome colleagues have been interacting with James Hendler of RPI. This also led us to an article from our Google colleagues ‘The unreasonable effectiveness of data’ by Halevy, Norvig, and Pereira. The best way to capture where all this fits versus what we are seeking in QuEST is a section in that article that draws the distinction between Semantic Web and Semantic Interpretation (if you will meaning – thanx Laurie F for keeping us focused on this key). Semantic web is a convention for formal representation languages that lets software services interact with each other without needing AI (or any of the meaning making we’ve discussed in QuEST). Services interact because they use the same standard OR known translations into a chosen standard – it is for ‘comprehending’ appropriately constructed semantic documents / data NOT understanding human speech / writings that haven’t been so constructed – that is the semantic interpretation problem which requires imprecise, ambiguous natural language. ** I clearly have issues with their use of the term ‘comprehending’ in that it is a form of rigidly defining pieces of documents and/or data so they can be combined in a rigorously defined manner and I don’t consider that ‘comprehension’ by the software that code embodies the comprehension of a predefined set of activities that should be allowed with these entries** The semantics in Semantic web is in the code that implements the services in accordance with the pre-wired specifications expressed by accepted ontologies and documentation on appropriate / acceptable manipulation of entries. The semantics in semantic interpretation is associated with meaning to a human as embodied in human cognitive and cultural processes…the goal of QuEST is to engineer computer agents that capture some of the ‘comprehension’ characteristics of human agents to include both intuitive (Type 1) and conscious (Type 2) aspects. We do NOT restrict the semantic aspects to the type 2 and our discussions on big data has captured what we can expect it to provide along the Type 1 axes.

2.) The second topic we want to hit maybe this week is the generation of symbolic representations – for QuEST we are talking the vocabulary of working memory, Qualia. We want to review an article provided to our colleague Sandy V by Prof Ron Sun. Autonomous generation of symbolic representations through subsymbolic activities Ron Sun Version of record first published: 04 Sep 2012. …This paper explores an approach for autonomous generation of symbolic representations from an agent’s subsymbolic activities within the agent-environment interaction. The paper describes a psychologically plausible general framework and its various methods for autonomously creating symbolic representations. The symbol generation is accomplished within, and is intrinsic to, a generic and comprehensive cognitive architecture for capturing a wide variety of psychological processes (namely, CLARION). This work points to ways of obtaining more psychologically/cognitively realistic symbolic and subsymbolic representations within the framework of a cognitive architecture, and accentuates the relevance of such an approach to cognitive science and psychology.

3.) Also I would like to point out an article we reviewed this week associated with the use of Google Glass for physiological parameter estimation – BioGlass: Physiological Parameter Estimation Using a Head-mounted Wearable Device – by Hernandez et al.

4.) Also we would like to revisit our discussion on Qualia based tracking and extend the ideas discussed to include Qualia based representations for Cyber Operations – we would like to take the proposed work by our colleague Mike R and brainstorm where / how a qualia based representation could play similar to our previous tracking discussion.

Weekly QuEST Discussion Topics and News, 12 Sept

September 11, 2014 Leave a comment

QuEST 12 Sept 2014:

1.) We want to start by addressing a comment made at the end of last week by our colleague Qing W from Rome on Semantic Web efforts and specifically how they relate to ‘big-data’ and how they both relate to QuEST. I’ve spent some time this week updating our Big data and QuEST slides to include capturing up front many of the walk-aways. We have previously (several years ago) gone down this semantic web path but it is worth revisiting where semantic web work fits. Our Rome colleagues have been interacting with James Hendler of RPI. We want to hit some of his presentations and discuss – this also led us to an article from our Google colleagues ‘The unreasonable effectiveness of data’ by Halevy, Norvig, and Pereira. The best way to capture where all this fits versus what we are seeking in QuEST is a section in that article that draws the distinction between Semantic Web and Semantic Interpretation (if you will meaning – thanx Laurie F for keeping us focused on this key). Semantic web is a convention for formal representation languages that lets software services interact with each other without needing AI (or any of the meaning making we’ve discussed in QuEST). Services interact because they use the same standard OR known translations into a chosen standard – it is for ‘comprehending’ appropriately constructed semantic documents / data NOT understanding human speech / writings that haven’t been so constructed – that is the semantic interpretation problem which requires imprecise, ambiguous natural language. ** I clearly have issues with their use of the term ‘comprehending’ in that it is a form of rigidly defining pieces of documents and/or data so they can be combined in a rigorously defined manner and I don’t consider that ‘comprehension’ by the software that code embodies the comprehension of a predefined set of activities that should be allowed with these entries** The semantics in Semantic web is in the code that implements the services in accordance with the pre-wired specifications expressed by accepted ontologies and documentation on appropriate / acceptable manipulation of entries. The semantics in semantic interpretation is associated with meaning to a human as embodied in human cognitive and cultural processes…the goal of QuEST is to engineer computer agents that capture some of the ‘comprehension’ characteristics of human agents to include both intuitive (Type 1) and conscious (Type 2) aspects. We do NOT restrict the semantic aspects to the type 2 and our discussions on big data has captured what we can expect it to provide along the Type 1 axes.

2.) The second topic we want to hit maybe this week is the generation of symbolic representations – for QuEST we are talking the vocabulary of working memory, Qualia. We want to review an article provided to our colleague Sandy V by Prof Ron Sun. Autonomous generation of symbolic representations through subsymbolic activities Ron Sun Version of record first published: 04 Sep 2012. …This paper explores an approach for autonomous generation of symbolic representations from an agent’s subsymbolic activities within the agent-environment interaction. The paper describes a psychologically plausible general framework and its various methods for autonomously creating symbolic representations. The symbol generation is accomplished within, and is intrinsic to, a generic and comprehensive cognitive architecture for capturing a wide variety of psychological processes (namely, CLARION). This work points to ways of obtaining more psychologically/cognitively realistic symbolic and subsymbolic representations within the framework of a cognitive architecture, and accentuates the relevance of such an approach to cognitive science and psychology.

3.) Also I would like to point out an article we reviewed this week associated with the use of Google Glass for physiological parameter estimation – BioGlass: Physiological Parameter Estimation Using a Head-mounted Wearable Device – by Hernandez et al.

news summary (1)

Weekly QuEST Discussion Topics and News, 5 Sept

September 4, 2014 Leave a comment

1.)  The first topic has to do with the current debate on ISIS / ISIL – we want to wrap in a few extra points that came up last week – and integrate them into the ‘think piece’ – specifically the connection to things like Ferguson Mo and also Rik W brought up the mechanisms used in Bee Hives to keep them healthy (how they eliminate the old / sick / weak.  So I again want to discuss is there a common theme that is consistent with our think piece –  Fighting an Adaptable foe.  Specifically the common issues in fighting in cyber, fighting the war on cancer and the fight against terrorism – now adding the mechanisms nature uses to maintain healthy societies like beehives and also social unrest like Ferguson Mo.  Recall our interest in this topic started by an article in the area of the fight against cancer the basic idea — still in the experimental stages — is that cancer cells cannot turn into a lethal tumor without the cooperation of other cells nearby. That may be why autopsies repeatedly find that most people who die of causes other than cancer have at least some tiny tumors in their bodies that had gone unnoticed.  *** in fact confirms matt’s brothers observation – and the lung cancer observation – that found as many lung cancers in nonsmokers although clearly more smokers die from lung cancer *** According to current thinking, the tumors were kept in check, causing no harm. … It also may mean that cancers grow in part because normal cells surrounding them allowed them to escape. It also means that there might be a new way to think about treatment: cancer might be kept under control by preventing healthy cells around it from crumbling*** this is the provide security and safety strategy approach to asymmetric war ***…“Think of it as this kid in a bad neighborhood,” said Dr. Susan Love, a breast cancer surgeon and president of the Dr. Susan Love Research Foundation. “You can take the kid out of the neighborhood and put him in a different environment and he will behave totally differently.” We also had to point of using insecticides attack pests in agriculture.

2.)   The second topic is we’ve recently had an open technical workshop on Sensing as a Service.  As part of that workshop we developed a list of actionable characteristics of SaaS solutions.  A discussion of where QuEST can impact these efforts would be interesting. 

3.)  The last topic, if we make it to it, is associated with our recent discussions on ‘big data’.  Over the last couple of weeks we’ve developed a  position of where/how QuEST fits with respect to big data efforts.  I would like to have a discussion on the walk-aways on big-data in general and specifically on QuEST and big data.  To have that discussion I would like to review ‘big data’ material we’ve reviewed over the last couple of years and pull it all together so people can catch up and comment.

Weekly QuEST Discussion Topics and News 5 Sept

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Weekly QuEST Discussion Topics and News, 29 Aug

August 28, 2014 Leave a comment

QuEST 29 Aug 2014:

1.)  The first topic has to do with the current debate on ISIS / ISIL.  It reminded me of a set of discussions that have happened over the last couple of years in the QuEST meetings and resulted in us putting together a ‘think piece’ on Fighting an Adaptable foe.  Specifically the common issues in fighting in cyber, fighting the war on cancer and the fight against terrorism.  In the area of the fight against cancer the basic idea — still in the experimental stages — is that cancer cells cannot turn into a lethal tumor without the cooperation of other cells nearby. That may be why autopsies repeatedly find that most people who die of causes other than cancer have at least some tiny tumors in their bodies that had gone unnoticed.  *** in fact confirms matt’s brothers observation – and the lung cancer observation – that found as many lung cancers in nonsmokers although clearly more smokers die from lung cancer ***According to current thinking, the tumors were kept in check, causing no harm. … It also may mean that cancers grow in part because normal cells surrounding them allowed them to escape. It also means that there might be a new way to think about treatment: cancer might be kept under control by preventing healthy cells around it from crumbling*** this is the provide security and safety strategy approach to asymmetric war ***…“Think of it as this kid in a bad neighborhood,” said Dr. Susan Love, a breast cancer surgeon and president of the Dr. Susan Love Research Foundation. “You can take the kid out of the neighborhood and put him in a different environment and he will behave totally differently.” … if there is interest we can revisit this ‘think piece’ to see if our newer QuEST ideas can impact differently now.

2.)   The second topic has to do with the discussion last week on how we do NOT think the solution to a general purpose artificial intelligence that can respond acceptably to the unexpected query is to learn the representation it is to learn/adapt the parameters of a simulation.  We are reminded in our interactions with Prof Geman – We have these quotes from his presentations he gave us:

The mind’s eye

  • The brain simulates
  • Representations must be nearly literal
  • We don’t learn representations; we learn the parameters of simulation (“strong priors”)

And

 

  • Nonparametric learning may have little or nothing to do with biological learning (ontogenetic & phylogenetic)
  • The advantages of simulation would explain the striking growth of the neocortex
  • The homogeneity of the cortex suggests repeatable and scalable rules of composition
  • Image understanding might be more a matter of constructing a scene model than of computing a classification

 

And with the work we discussed last week at QuEST that is all about classification / localization being where the big boys (google / facebook) are focused I think we are on an interesting path with QuEST … what I would like to discuss is finding relevant publications that attempt to attack the issue of the difference in learning the parameters for a simulation versus learning a representation?  How does this solve the Biederman problem?  And the answer to the Jared question – what are the parameters of the simulation? (to me they are the qualia – the vocabulary of conscious thought)

 

3.)  That brings us to the third topic – another Prof we’ve interacted with that inspired us to continue down the path of the conscious representation is a simulation versus a projection of sensory data – Prof Barsalou – a key attribute of simulation is the pattern completion inferencing – I would like to present his work that provides an interesting explanation of mirror neurons related to simulation – Mirroring as Pattern Completion Inferences within Situated Conceptualizations – … The classic account of mirroring is that it results from mirror neurons, namely, neurons that have both motor and perceptual tunings. Mirror neurons not only become active when an action is performed, but also when it is perceived.  Because these neurons become active during the perception of an action, they ground the perception in action simulation. An alternative account constitutes the thesis developed here: Mirroring is a special case of a basic cognitive process common across species, namely, Pattern Completion Inferences …  within Situated Conceptualizations (PCIwSC). According to PCIwSC, the brain is a situation processing architecture (Barsalou, 2003, 2009; Barsalou et al., 2003; Wilson-Mendenhall et al., 2011; Yeh and Barsalou, 2006).

Weekly QuEST Discussion Topics and News 29 Aug

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Weekly QuEST Discussion Topics and News, 22 Aug

August 21, 2014 Leave a comment

QuEST 22 Aug 2014

There are several news stories that we need to cover – the first is the recent LSCRC – large scale visual recognition challenge:

Started in 2010 by Stanford, Princeton and Columbia University scientists, the Large Scale Visual Recognition Challenge this year drew 38 entrants from 13 countries. The groups use advanced software, in most cases modeled loosely on the biological vision systems, to detect, locate and classify a huge set of images taken from Internet sources like Twitter. The contest was sponsored this year by Google, Stanford, Facebook and the University of North Carolina.

Contestants run their recognition programs on high-performance computers based in many cases on specialized processors called G.P.U.s, for graphic processing units.

This year there were six categories based on object detection, locating objects and classifying them. Winners included the National University of Singapore, the Oxford University, Adobe Systems, the Center for Intelligent Perception and Computing at the Chinese Academy of Sciences, as well as Google in two separate categories.

Accuracy almost doubled in the 2014 competition and error rates were cut in half, according to the conference organizers.

… This year performance took a big leap …

Despite the fact that contest is based on pattern recognition software that can be “trained” to recognize objects in digital images, the contest itself is made possible by the Imagenet database, an immense collection of more than 14 million images that have been identified by humans. The Imagenet database is publicly available to researchers at http://image-net.org/.

In the five years that the contest has been held, the organizers have twice, once in 2012 and again this year, seen striking improvements in accuracy, accompanied by more sophisticated algorithms and larger and faster computers.

… This year almost all of the entrants used a variant of an approach known as a convolutional neural network, an approach first refined in 1998 by Yann LeCun, a French computer scientist who recently became director of artificial intelligence research at Facebook.

“This is LeCun’s hour,” said Gary Bradski, an artificial intelligence researcher who was the founder of Open CV, a widely used machine vision library of software tools. Convolutional neural networks have only recently begun to have impact because of the sharply falling cost of computing, he said, “In the past there were a lot of things people didn’t do because no one realized there would be so much inexpensive computing power available.”

The accuracy results this year improved to 43.9 percent, from 22.5 percent, and the error rate fell to 6.6 percent, from 11.7 percent, according to Olga Russakovsky, a Stanford University graduate researcher who is the lead organizer for the contest. Since the Imagenet Challenge began in 2010, the classification error rate has decreased fourfold, she said.

… “Human-level understanding is much deeper than machine image classification,” she said. “I can easily find a image that will fool the algorithm and I can’t do it with humans, but we’re making significant progress.”

Although machines have made great progress in object recognition, they are only taking baby steps in what scientists describe as “scene understanding,” the ability to comprehend what is happening in an image in human language.

“I really believe in the phrase that ‘a picture is worth a thousand words,’ not a thousand disconnected words,” said Dr. Li. ”It’s the ability to tell a complete story. That is the holy grail *** meaning making **

This last piece is where we want to discuss – where we have been many times before – what is ‘meaning making’ and how it is agent centric – and how does QuEST play in this space

Next there was a couple of articles on Big Data (one focused on healthcare and one on ‘data wrangling’) the places where QuEST and Big Data merge might be in these areas – in both cases we need to understand the role of the human/computer agents.

The last news article I want to hit briefly is the ‘man playing the violin while undergoing brain surgery’ – we have hit related topics recently when discussing whether consciousness can initiate action or not (also we’ve discussed the Penfield work).

Also I want to briefly hit a recent article that our colleague Sandy V brought to our attention on narratives and expertise. Modeling the Function of Narrative in Expertise by W. Korey MacDougall, Robert L. West, and Christopher Genovesi

• The use of narrative is ubiquitous in the development, exercise, and communication of expertise.

• Expertise and narrative, as complex cognitive capacities, have each been investigated quite deeply, but little attention has been paid to their interdependence. We offer here the position that treating these two domains together can fruitfully inform the modeling of expert cognition and behavior, and present the framework we have been using to develop this approach, the SGOMS macro-cognitive architecture. Finally, we briefly explore the role of narrative in an SGOMS model of cooperative video game playing.
news summary (7)

Weekly QuEST Discussion Topics and News, 15 Aug

August 14, 2014 Leave a comment

Weekly QuEST Discussion Topics

 15 Aug 2014

The first topic is an article from the news stories this week – ‘Forget Siri: this Radical New AI Teaches itself and reads your mind’ – by Steven Levy, it discusses Viv which is an attempt to overcome the limitations of digital assistant software associated to only being able to respond / perform tasks that have specifically been implemented by the designing engineers.  Viv does this by teaching itself and capturing the new ‘thoughts’ by writing its own new code.  It also captures a representation of a particular user so it can generate anticipatory actions.  QuEST needs to discuss this work from several angles.  The limitations of current solutions helps us refine our thoughts on ‘unexpected queries’.  We want to look at some of the examples provided and discuss how a conscious agent solves them and how an artificially conscious QuEST agent could hope to bring value. 

http://www.wired.com/2014/08/viv/?mbid=social_fb

 

Forget Siri: This Radical New AI Teaches Itself and Reads Your Mind

 

The next topic is a brief discussion about a short article provided by our colleague Robert P.  ‘Thinking about thinking’.  It stimulated an exchange where we revisited a prior tenet discussion where Prof Oxley pointed out to us that there had been a mathematical proof we needed to consider about self referential systems – to resulting discussion led to our addition of the following tenet:

 

Thinking about thinking:  A mathematical proof has been constructed that theorizes it is impossible to think about yourself thinking.  This is consistent with the ‘One quale at a time’ tenet which suggests that you can only think about having thought.  You can only be conscious of having been conscious.  You are never conscious of being conscious.

 

This brings up the question of accounting for meta-cognition.  We might want to have this discussion.

Next there was a request for publications from our group from a journal Philosophy Study.  While looking through the journal we noticed an article by Deepak Chopra: ‘From Quanta to Qualia: How a paradigm Shift Turns Into Science’.  Our colleague Mike Y and Capt Amerika have read through the article and we might spend a couple minutes talking about the area of Panpsychism and how QuEST would respond.

Lastly if there is time there are several articles from the computational models of narratives conference that caught our eye.  We might go through a couple of them if they turn out to be interesting from a QuEST implementation perspective.  The first is Modeling the Function of Narrative in Expertise by MacDougall et al.

Abstract: The use of narrative is ubiquitous in the development, exercise, and communication of expertise.  Expertise and narrative, as complex cognitive capacities, have each been investigated quite deeply,

but little attention has been paid to their interdependence. We offer here the position that treating these two domains together can fruitfully inform the modeling of expert cognition and behavior, and present the framework we have been using to develop this approach, the SGOMS macro-cognitive architecture. Finally, we briefly explore the role of narrative in an SGOMS model of cooperative video game playing.

news summary (5)

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CSE/EID Workshop

August 14, 2014 Leave a comment

See below here for details on a workshop on Cognitive Systems Engineering (CSE) and Ecological Interface Design (EID), as presented by Dr. John Flach and Dr. Kevin Bennett.

Workshop Supporting Productive Thinking through Interface Design

This workshop is designed to introduce researchers and practitioners to the Cognitive
Systems Engineering (CSE) paradigm and the implications for the design of interfaces
to support problem solving in complex work domains (Ecological Interface Design –
EID). Basic assumptions about the pragmatic nature of reasoning (i.e., problem solving
and decision making) in complex work domains will be presented. The CSE/EID
framework provides a holistic systems perspective for addressing a wide range of
issues associated with performance in sociotechnical systems (e.g., workload,
situation awareness, trust, distributed collaboration, resilience, etc.). Particular
attention will be paid to the implications for the design of interface representations
that enhance perspicacity with respect to the deep structure of work domains in order
to support productive thinking.

Where: Building 441 Auditorium
When: Wednesday, August 20, 2014; 0900-1230
Who:
Kevin Bennett and John Flach recently co-authored the text Display and Interface Design.
This text is the culmination of a nearly 25 year collaboration to explore Cognitive Systems
Engineering as an alternative approach for leveraging human capabilities to achieve skilled
control in complex work environments. Their approach has been praised for the ability to
link basic theories from ecological psychology/situated cognition to innovative design
solutions

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