Weekly QuEST Discussion Topics and News, 25 July

QuEST July 25, 2014

The first topic this week is to allow our colleague Sandy V to present her 10 min talk for the upcoming Computational Models of Narratives conference – then open the floor for 10 min questions she might get asked – then come constructive comments on possible changes to her slides/presentation –

Abstract for ‘Narratives as a Fundamental Component of Consciousness’

In this paper, we propose a conceptual architecture that models human (spatially-temporally-modally) cohesive narrative development using a computer representation of quale properties. Qualia are proposed to be the fundamental cognitive components humans use to generate cohesive narratives. The engineering approach is based on cognitively inspired technologies and incorporates the novel concept of quale representation for computation of primitive cognitive components of narrative. The ultimate objective of this research is to develop an architecture that emulates the human ability to generate cohesive narratives with incomplete or perturbated information.

In a related topic area:

Working with Sandy / Lizzy this week it became obvious we need to carefully revisit our definitions of consciousness and qualia – so I review of the material that most closely aligns to our use of the terms is useful – and for that we commonly have used the dissertation of the John Searle student Cowell –

The next topic is a couple of articles provided to us by our colleague Robert P. –

The mind’s best trick:
how we experience conscious will
Daniel M. Wegner

• We often consciously will our own actions. This experience is so profound that it tempts us to believe that our actions are caused by consciousness.
• It could also be a trick, however – the mind’s way of estimating its own apparent authorship by drawing causal inferences about relationships between thoughts and actions.
• Cognitive, social, and neuropsychological studies of apparent mental causation suggest that experiences of conscious will frequently depart from actual causal processes and so might not reflect direct perceptions of conscious thought causing action.

Johansson, P., Hall, L., Sikström, S., & Olsson, A. (2005). Failure to detect
mismatches between intention and outcome in a simple decision task.
Science (New York, N.Y.), 310(5745), 116–9. doi:10.1126/science.1111709

• A fundamental assumption of theories of decision-making is that we detect mismatches between intention and outcome, adjust our behavior in the face of error, and adapt to changing circumstances. Is this always the case? We investigated the relation between intention, choice, and introspection. Participants made choices between presented face pairs on the basis of attractiveness, while we covertly manipulated the relationship between choice and outcome that they experienced. Participants failed to notice conspicuous mismatches between their intended choice and the outcome they were presented with, while nevertheless offering introspectively derived reasons for why they chose the way they did. We call this effect choice blindness.

Weekly QuEST Discussion Topics and News 25 July

Weekly QuEST Discussion Topics and News, 18 July

QuEST 18 July 2014

1.) We will continue discussing some work by our colleagues in the Sensors directorate associated with QuEST applications to SAR and EO data exploitation and specifically tracking. The QuEST position going in is that a dual process tracker (Type 1 and Type 2 components) can out-perform a single process data driven tracker – but this week I want to caveat this statement – it is not clear to me that a Qualia based tracker should outperform a data based tracker on a measure of track accuracy – maybe what we should expect is a qualia based tracker is more robust (holding onto tracks under dramatic variations in lighting / weather and that it requires far less computational bandwidth (recall the 50 bits/sec throughput sub-tenet)) – … the point being we need to discuss what we would expect to gain by a Qualia based tracking more carefully. I suggested that advances like feature aided tracking (FAT) and context aided tracking (CAT) support the position that more than kinematics is required in more complicated operating conditions. But I would suggest that a better Type 2 representation, more QuEST like could do even better since it would not be so bound to the variations in the data – and thus the need to define these measures – the idea being like we’ve pushed for QuEST solutions as an approach to reduce the space of the unexpected query – so for tracking we need to define the UQ – and that will be those operating conditions where current approaches to tracking don’t generate acceptable responses / outputs – then blend these with the qualia based tracking to demonstrate improved performance through these previously problematic operating conditions thus demonstrating the reduction in the UQ space. But current approaches using those ideas are still focused in the measured data world versus attempting to generate a hypothetical representation simulation based / situation / structurally coherent representation and blending that with the data driven tracking. Work that attempts to track through obscurations were a start consistent with this idea– but again they do not attempt to use our guiding tenets for the add-on representation / processes.

a. The SAR / EO fusion aspect should also be considered – the fact that at the ‘cartoon’ level entities and their relationships are all that matters and the sensing modality that the source information came from is washed away – at the cartoon level qualia are defined by their relationships with and how they can / do interact with other qualia – and even this representation should be squeezed to force maximal compression while still providing acceptable responses for the operating conditions experienced – so in an EO image the quale that is associated with a given vehicle moving down the road at a particular Geo location at a particular time but keep in mind in qualia space aspects like geo – location and even time are qualia and are only defined by how they are related to other qualia and how they can interact with other qualia – and they are only experienced when they are the source of the experience -> they are the source of the qualia used to achieve the goal of tracking – so let’s take an EO image and define all the qualia that could be evoked from it (then squeeze down to a subset that allows maintaining track – keeping in mind this image is not taken out of context – it is taken as one image in a sequence of data (EO and SAR) – but within the frame there are blobs – we have defined blobs before as parts of a sensory steam that are submitted for qualiarization based upon their brightness / color / motion / texture for example in the visual stream – since one of the means to blob part of the sensory data is to attach to a portion of the stream a cohesive movement relative to parts of the data stream adjacent to it

2.) The discussion above also suggest we need to return to our previous discussions on ‘meaning’, ‘blobs’ and computing with qualia

3.) Another topic that came up this week is work within the Human Effectiveness directorate on ‘synthetic team-mate’ – we want to have a discussion about that data and its potential use in our research.

news summary (4)

Weekly QuEST Discussion Topics and News, July 11

1.) We will start by discussing some work by our colleagues in the Sensors directorate associated with QuEST applications to SAR and EO data exploitation and specifically tracking. The QuEST position going in is that a dual process tracker (Type 1 and Type 2 components) can our perform a single process data driven tracker. I would suggest that advances like feature aided tracking (FAT) and context aided tracking (CAT) support this position. But I would suggest that a better Type 2 representation, more QuEST like could do even better since it would not be so bound to the variabilities of the data. But current approaches using those ideas are still focused in the measured data world versus attempting to generate a hypothetical representation and blending that with the data driven tracking. Work that attempts to track through obscurations uses this idea and then often confirms the results using features / context – but again they do not attempt to use our guiding tenets for the add-on representation / processes.
2.) We also want to discuss some of the ideas in the current draft of the Erik Blasch led effort for an article for NAECON. *** we might defer much of this discussion as Eric will be out on Fridaywelcoming into the world his new child! ** His bold attempt to get down on paper how what we are doing is related to fusion and narratives inspired some dialogue that the group may want to chime in on. The first topic is where does QuEST fit in the mission space when we are talking PCPAD. Specifically can we achieve an artificially conscious decision aid if we don’t allow that agent / agents the ability to interact with the sensing apparatus. Another topic is where does QuEST fit in the levels of information fusion – there are some obvious places but maybe we need to articulate how it could fit at all of the levels and thus be more integrated in the system of systems. Then there is the discussion of activity based intelligence versus object based production versus a far more general approach to ‘event based content management’ or what I would like to call ‘Qualia based content management’. Then there is the discussion on mapping our construct onto the situational awareness levels. Then explaining the QuEST tenets in a manner a non-QuEST person could get the gist of them. Eventually leading to a QuEST model for information fusion.
3.) The third topic is a continuation of the discussion of implementing QuEST solutions using existing cognitive architectures and their infrastructures. Last week we discussed briefly a recent publication by one of our colleagues Robert Patterson and Kennedy – Modeling Intuitive Decision Making in ACT-R. the reason I want to discuss that article is it has many of the facets we’ve been discussing associated with the proposed work of our colleague Sandy V. specifically we want to use the Patterson approach to interfacing a virtual world to ACT-R and some of their use of the existing ACT-R modules.
a. Abstract: One mode of human decision-making is considered intuitive i.e., unconscious situational pattern recognition. Implicit statistical learning, which involves the sampling of invariances from the environment and is known to involve procedural (i.e., non-declarative) memory, has been shown to be a foundation of this mode of decision making. We present an ACT-R model of implicit learning whose implementation entailed a declarative memory-based learner of the classification of example strings of an artificial grammar. The model performed very well when compared to humans. The fact that the simulation of implicit learning could not be implemented in a straightforward way via a non-declarative memory approach, but rather required a declarative memorybased implementation, suggests that the conceptualization of procedural memory in the ACT-R framework may need to be expanded to include abstract representations of statistical regularities. Our approach to the development and testing of models in ACT-R can be used to predict the development of intuitive decision-making in humans.
4.) We want to extend the discussion this week to include another Kennedy article that implements dual process solution using ACT-R. ‘Integrating Fast and Slow Cognitive Processes’
a. Abstract – Human reactions appear to be controlled by two separate types of mental processes: one fast, automatic, and unconscious and the other slow, deliberate, and conscious. With the attention in the literature focused on the taxonomy of the two processes, there is little discussion of how they interact. In this paper, we focus on modeling the slower process’s ability to inhibit the fast process. We present computational cognitive models in which different strategies allow a human to consciously inhibit an undesirable fast response. These general strategies include (a) blocking sensory input, (b), blocking or interrupting the fast process’s response, and (c) slowing down or delaying processing by introducing additional task. Furthermore, we discuss an approach to learning such strategies based on the inference of the causes and effects of the fast process.

Weekly QuEST Discussion Topics and News July 11

Weekly QuEST Discussion Topics and News, 3 July

1.) We want to start this week discussing modern approaches to collaboration – specifically we’ve asked our colleague Dan Uppencamp to come in and discuss with us his Google embedding time and the tools he used (Google apps) while working in the Earth Engine group out at Mountain View. The reason we want to have this discussion is I would like to encourage us to attempt to use those tools in the development of the QuEST white paper and some of our QuEST research probably using the RDT&E network versus NIPR.
2.) The Second topic is a continuation of the discussion of implementing QuEST solutions using existing cognitive architectures and their infrastructures. This week I’m excited to discuss a recent publication by one of our colleagues Robert Patterson – Modeling Intuitive Decision Making in ACT-R. the reason I want to discuss that article is it has many of the facets we’ve been discussing associated with the proposed work of our colleague Sandy V. specifically we want to use the Patterson approach to interfacing a virtual world to ACT-R and some of their use of the existing ACT-R modules.
a. Abstract: One mode of human decision-making is considered intuitive i.e., unconscious situational pattern recognition. Implicit statistical learning, which involves the sampling of invariances from the environment and is known to involve procedural (i.e., non-declarative) memory, has been shown to be a foundation of this mode of decision making. We present an ACT-R model of implicit learning whose implementation entailed a declarative memory-based learner of the classification of example strings of an artificial grammar. The model performed very well when compared to humans. The fact that the simulation of implicit learning could not be implemented in a straightforward way via a non-declarative memory approach, but rather required a declarative memorybased implementation, suggests that the conceptualization of procedural memory in the ACT-R framework may need to be expanded to include abstract representations of statistical regularities. Our approach to the development and testing of models in ACT-R can be used to predict the development of intuitive decision-making in humans.

Weekly QuEST Discussion Topics and News 3 July

Weekly QuEST Discussion Topics, 27 June

Our main topic this week is how to modify existing cognitive architectures / models like the ACT-R model to be consistent with our Theory of Consciousness to include our view qualia and narratives – The work of one of our Colleagues Sandy V is driving this discussion – a discussion along these lines will also allow our colleagues going to the upcoming computational models of narratives workshop to focus their interactions to assist some of the current challenges we are facing on implementation as well as Sandy working on a cyber wingman and attempting to incorporate elements of our Theory of consciousness into those wingmen.

Weekly QuEST Discussion Topics and News 27 June

Weekly QuEST Discussion Topics, 24 June

We will meet on Tues 24 Jun at noon and on Friday 27 June at noon. We will not do the white paper discussions this week with our colleagues at the CVPR conference. Instead we will clean up any issues people would like to discuss. Two topics on the top of Capt Amerika’s list of concerns are:
1.) ACT-R / LaRue models and narratives – giving some thought ot how to tie these ideas together – a discussion along these lines will allow our colleagues going to the upcoming computational models of narratives workshop to focus their interactions to assist some of the current challenges we are facing on implementation.

2.) While working on his novel while at the beach – Capt Amerika realized the importance of ‘situating’ the reader as a key talen t good novelist have (unlike Capt Amerika) – as an engineer up to this point the novel (‘Taming the Beast’) – was full of anecdotes and short snippets of stories to communicate a series of life lessons on leadership – once he altered this approach and realized that when good novels are written what he previously considered fluff was really all about situating the reader – when you successfully situate the reader you are engaging both their Type 1 and their Type 2 processes and thus totally immerse them in the experience versus being told something second hand – if you will you have to get their mirror neurons working – he might provide a couple of examples from the book – this experience also has him rethinking the cloud diagram of our cognitive framework – clearly when you read something (like the novel) you are using your Type 2 processes to get the stimuli – but if appropriately written the Type 2 processes will not only help re-wire your Type 1 processes they engage your Type 1 processes (for example you get emotionally engaged into what you are reading) – it also seems that the multiple plausible narratives we’ve spoke of and recently talked instead of multiple potential cohesive narratives –really are not complete narratives but alternative emphasis being placed on the many potential links that are being used to create the working memory – our recent discussions on conceptual combination where we spoke of the many different ways that people have used to model this process

Weekly QuEST Discussion Topics and news, 12 June

First we want to talk schedule – There will be no meeting on 13 June, then the next meeting after that will be Tues 24 June then back to the Friday noon schedule on 27 June(sorry but due to Capt Amerika travelling the only other alternative is cancelling). Meetings on the 12 and the 24th will focus on discussions on topics of interest versus Capt Amerika providing a lecture on recent articles.

1.) The first discussion topic is on work in ‘conceptual combination’ – specifically we want to place the work recently presented on how it can be used (as could LASS and/or CIH) to address the ‘unexpected query’ – Conceptual combinationresearch investigates the processes involved in creating new meaning from old referents. It is therefore essential that embodied theories of cognition are able to explain this constructive ability and predict the resultant behavior. Article by Lynott – ‘Embodied conceptual combination – Frontiers in psychology nov 2010 vol 1 article 212
i. …, by failing to take an embodied or grounded view of the conceptual system, existing theories of conceptual combination cannot account for the role of perceptual, motor, and affective information in conceptual combination.
ii. In the present paper, we propose the embodied conceptual combination (ECCo) model to address this oversight.
iii. In ECCo, conceptual combination is the result of the interaction of the linguistic and simulation systems, such that linguistic distributional information guides or facilitates the combination process,but the new concept is fundamentally a situated, simulated entity.
2.) The second topic is on designing function models – specifically one of our colleagues is attempting to use existing models associated with the ACTR approach to implement a QuEST compliant solution. That has led to an interaction with Stanovich which led to some work that we’ve previously discussed by Sloman – so we want to re-look at the summary notes where we discussed Sloman and others on designing artificially conscious systems.
3.) We also of course will entertain any topic associated with the generation of the QuEST whitepaper.

Weekly QuEST Discussion Topics and News 12 June

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