Category Archives: Lit Review

Phil 7.19.19

7:00 – 4:30 ASRC GEOS


  • Still looking at what’s wrong with my NK model. I found Random Boolean Networks, when looking for “random binary networks kauffman example“. It also has a bibliography that looks helpful as well
    • Introduction to Random Boolean Networks
      • The goal of this tutorial is to promote interest in the study of random Boolean networks (RBNs). These can be very interesting models, since one does not have to assume any functionality or particular connectivity of the networks to study their generic properties. Like this, RBNs have been used for exploring the configurations where life could emerge. The fact that RBNs are a generalization of cellular automata makes their research a very important topic. The tutorial, intended for a broad audience, presents the state of the art in RBNs, spanning over several lines of research carried out by different groups. We focus on research done within artificial life, as we cannot exhaust the abundant research done over the decades related to RBNs.
      • I can add a display that shows this: Trajectory
      • Got that working
      • Rewrote so that there is an evolve without a fitness test. Trying to set up transition patterns like this: Transitions
      • The thing is, I don’t see how the K part works here…
      • I think I got it working!
    • Complex and Adaptive Dynamical Systems: A Primer
      • An thorough introduction is given at an introductory level to the field of quantitative complex system science, with special emphasis on emergence in dynamical systems based on network topologies. Subjects treated include graph theory and small-world networks, a generic introduction to the concepts of dynamical system theory, random Boolean networks, cellular automata and self-organized criticality, the statistical modeling of Darwinian evolution, synchronization phenomena and an introduction to the theory of cognitive systems. 
        It inludes chapter on Graph Theory and Small-World Networks, Chaos, Bifurcations and Diffusion, Complexity and Information Theory, Random Boolean Networks, Cellular Automata and Self-Organized Criticality, Darwinian evolution, Hypercycles and Game Theory, Synchronization Phenomena and Elements of Cognitive System Theory.

Phil 7.16.19

7:00 – 6:30ASRC GEOS

  • Working more on NK Models. I have the original paper – Towards a general theory of adaptive walks on rugged landscapes, and I’ve pulled out my copy of The Origins of Order
    • Determine if I have the evaluation function right
    • Add mutation
    • Draw the networks
    • Draw an N/K/Fitness landscape?
    • As an aside, I think that an NK model can be modified to use backpropagation rather than mutation. That could be interesting.
    • Ok, here’s everything working the way I think it should work, but I’m not sure it’s right….
  • Need to get back to Antonio about authorship and roles. I think that it makes sense if he can get a sense of what – done
  • Discovered the trumptwitterarchive, which is downloadable. Would like to build a network of the retweets and tagging by sentiment, gender and race.
  • Code review with Chris. Unfortunately, it was more like an interrogation than a tour. My sense is that he was expecting us to ask questions and we were expecting a presentation.
    • It went ok, but the audio connection was terrible

Phil 5.28.19

Phil 7:00 – 5:00 ASRC NASA GEOS

  • Factors Motivating Customization and Echo Chamber Creation Within Digital News Environments
    • With the influx of content being shared through social media, mobile apps, and other digital sources – including fake news and misinformation – most news consumers experience some degree of information overload. To combat these feelings of unease associated with the sheer volume of news content, some consumers tailor their news ecosystems and purposefully include or exclude content from specific sources or individuals. This study explores customization on social media and news platforms through a survey (N = 317) of adults regarding their digital news habits. Findings suggest that consumers who diversify their online news streams report lower levels of anxiety related to current events and highlight differences in reported anxiety levels and customization practices across the political spectrum. This study provides important insights into how perceived information overload, anxiety around current events, political affiliations and partisanship, and demographic characteristics may contribute to tailoring practices related to news consumption in social media environments. We discuss these findings in terms of their implications for industry, policy, and theory
  • More JASSS paper
  • Installing new IntelliJ and re-indexing
  • Discovered a few bugs with the JsonUtils.find. Fixed and submitted a version to StackOverflow. Eeeep!

Phil 5.13.19

7:00 – 3:00 ASRC NASA GEOS-R

Phil 5.6.19

7:00 – 5:00 ASRC GOES-R

  • Finished the AI/ML paper with Aaron M over the weekend. I need to have him ping me when it goes in. I think it turned out pretty well, even when cut down to 7 pages (with references!! Why, IEEE, why?)
    • Sent a copy to Wayne, and distributed around work. Need to put in on ArXiv on Thursday
  • Starting to pull parts from to make the lit review for the dissertation. Those reviews may have had a reason after all!
    • And oddly (though satisfying), I wound up adding a section on Moby-Dick as a way of setting up the rest of the lit review
  • More Matrix scalar class. Basically a satisfying day of just writing code.
  • Need to fix IEEE letter and take a self-portrait. Need to charge up the good camera

Phil 5.1.19

7:00 – 7:00 ASRC NASA AIMS

  • Added lit review section to the dissertation, and put the seven steps of sectarianism in.
  • Spent most of yesterday helping Aaron with TimeSeriesML. Currently working on a JSON util that will get a value on a provided path
  • Had to set up python at the module and not project level, which was odd. Here’s how:
  • Done!
        def lfind(self, query_list:List, target_list:List, targ_str:str = "???"):
            for tval in target_list:
                if isinstance(tval, dict):
                    return self.dfind(query_list[0], tval, targ_str)
                elif tval == query_list[0]:
                    return tval
        def dfind(self, query_dict:Dict, target_dict:Dict, targ_str:str = "???"):
            for key, qval in query_dict.items():
                # print("key = {}, qval = {}".format(key, qval))
                tval = target_dict[key]
                if isinstance(qval, dict):
                    return self.dfind(qval, tval, targ_str)
                elif isinstance(qval, list):
                    return self.lfind(qval, tval, targ_str)
                    if qval == targ_str:
                        return tval
                    if qval != tval:
                        return None
        def find(self, query_dict:Dict):
            # pprint.pprint(query_dict)
            result = self.dfind(query_dict, self.json_dict)
            return result
  • It’s called like this:
    ju = JsonUtils("../../data/output_data/lstm_structure.json")
    # ju.pprint()
    result = ju.find({"config":[{"class_name":"Masking", "config":{"batch_input_shape": "???"}}]})
    print("result 1 = {}".format(result))
    result = ju.find({"config":[{"class_name":"Masking", "config":{"mask_value": "???"}}]})
    print("result 2 = {}".format(result))
  • Here’s the results:
    result 1 = [None, 12, 1]
    result 2 = 666.0
  • Got Aaron’s code running!
  • Meeting with Joel
    • A quicker demo that I was expecting, though I was able to walk through how to create and use Corpus Manager and LMN. Also, we got a bug where the column index for the eigenvector didn’t exist. Fixed that in
  • Meeting with Wayne
    • Walked through the JASSS paper. Need to make sure that the lit review is connected and in the proper order
    • Changed the title of the dissertation to
      • Stampede Theory: Mapping Dangerous Misinformation at Scale
    • Solidifying defense over the winter break, with diploma in the Spring
    • Mentioned the “aikido with drones” concept. Need to make an image. Actually, I wonder if there is a way for that model to be used for actually getting a grant to explore weaponized AI in a way that isn’t directly mappable to weapons systems, but is close enough to reality that people will get the point.
    • Also discussed the concept of managing runaway AI with the Sanhedrin-17a concept, where unanimous agreement to convict means acquittal.  Cities had Sanhedrin of 23 Judges and the Great Sanhedrin had 71 Judges
      • Rav Kahana says: In a Sanhedrin where all the judges saw fit to convict the defendant in a case of capital law, they acquit him. The Gemara asks: What is the reasoning for this halakha? It is since it is learned as a tradition that suspension of the trial overnight is necessary in order to create a possibility of acquittal. The halakha is that they may not issue the guilty verdict on the same day the evidence was heard, as perhaps over the course of the night one of the judges will think of a reason to acquit the defendant. And as those judges all saw fit to convict him they will not see any further possibility to acquit him, because there will not be anyone arguing for such a verdict. Consequently, he cannot be convicted.


Phil 4.29.19

7:00 – 3:30 ASRC TL

  • Register for Tech Summit – done
  • Ask for a week of time to prep for talk – done
  • Panos read the paper and has some suggestions. Need to implement
  • This might be important: Neural Logic Machines
    • We propose the Neural Logic Machine (NLM), a neural-symbolic architecture for both inductive learning and logic reasoning. NLMs exploit the power of both neural networks—as function approximators, and logic programming—as a symbolic processor for objects with properties, relations, logic connectives, and quantifiers. After being trained on small-scale tasks (such as sorting short arrays), NLMs can recover lifted rules, and generalize to large-scale tasks (such as sorting longer arrays). In our experiments, NLMs achieve perfect generalization in a number of tasks, from relational reasoning tasks on the family tree and general graphs, to decision making tasks including sorting arrays, finding shortest paths, and playing the blocks world. Most of these tasks are hard to accomplish for neural networks or inductive logic programming alone.
  • Need to read the Nature “Behavior” paper. Notes probably go straight into the dissertation lit review – done
  • Continuing to read Army of None, which is ridiculously good. This figure has been making me think: AoN This implies that the idea that a set of diverse ML systems all agreeing is a warning condition is worth exploring.
  • Finished read through of Tao’s paper
  • Need to find a cardiologist for Arpita

Phil 4.23.19

7:00 – 5:30 ASRC TL

  • Reading Army of None and realizing that incorporating AI is a stampede theory and diversity issue:
    • This makes Aegis less like a finished product with a few different modes and more like a customizable system that can be tailored for each mission. Galluch explained that the ship’s doctrine review board, consisting of the officers and senior enlisted personnel who work on Aegis, begin the process of writing doctrine months before deployment. They consider their anticipated missions, intelligence assessments, and information on the region for the upcoming deployment, then make recommendations on doctrine to the ship’s captain for approval. The result is a series of doctrine statements, individually and in packages, that the captain can activate as needed during deployment. (Page 164)
    • Doctrine statements are typically grouped into two general categories: non-saturation and saturation. Non-saturation doctrine is used when there is time to carefully evaluate each potential threat. Saturation doctrine is needed if the ship gets into a combat situation where the number of inbound threats could overwhelm the ability of operators to respond. “If World War III starts and people start throwing a lot of stuff at me,” Galluch said, “I will have grouped my doctrine together so that it’s a one-push button that activates all of them. And what we’ve done is we’ve tested and we’ve looked at how they overlap each other and what the effects are going to be and make sure that we’re getting the defense of the ship that we expect.” This is where something like Auto-Special comes into play, in a “kill or be killed” scenario, as Galluch described it. (Page 164)
    • Extensive testing goes into ensuring that it works properly. Once the ship arrives in theater, the first thing the crew does is test the weapons doctrine to see if there is anything in the environment that might cause it to fire in peacetime, which would not be good. This is done safely by enabling a hardware-level cutout called the Fire Inhibit Switch, or FIS. The FIS includes a key that must be inserted for any of the ship’s weapons to fire. When the FIS key is inserted, a red light comes on; when it is turned to the right, the light turns green, meaning the weapons are live and ready to fire. When the FIS is red—or removed entirely—the ship’s weapons are disabled at the hardware level. (Page 165)
    • But the differences run deeper than merely having more options. The whole philosophy of automation is different. With Aegis, the automation is used to capture the ship captain’s intent. In Patriot, the automation embodies the intent of the designers and testers. The actual operators of the system may not even fully understand the designers’ intent that went into crafting the rules. The automation in Patriot is largely intended to replace warfighters’ decision-making. In Aegis, the automation is used to capture warfighters’ decision-making. (Page 165)
    • Hawley argued that Army Patriot operators train in a “sham environment” that doesn’t accurately simulate the rigors of real-world combat. As a result, he said “the Army deceives itself about how good their people really are. . . . It would be easy to believe you’re good at this, but that’s only because you’ve been able to handle the relatively non-demanding scenarios that they throw at you.” Unfortunately, militaries might not realize their training is ineffective until a war occurs, at which point it may be too late. (Page 171)
    • Hawley explained that the Aegis community was partially protected from this problem because they use their system day in and day out on ships operating around the globe. Aegis operators get “consistent objective feedback from your environment on how well you’re doing,” preventing this kind of self-deception. The Army’s peacetime operating environment for the Patriot, on the other hand, is not as intense, Hawley said. “Even when the Army guys are deployed, I don’t think that the quality of their experience with the system is quite the same. They’re theoretically hot, but they’re really not doing much of anything, other than just monitoring their scopes.” Leadership is also a vital factor. “Navy brass in the Aegis community are absolutely paranoid” about another Vincennes incident, Hawley said. (Page 171)
  • Working on JASS paper
  • Working on AI paper
  • Long chat with Eric H

Phil 4.22.19

7:00 – 4:00 ASRC TL

    • The mission of the Conference on Truth and Trust Online (TTO) is to bring together all parties working on automated approaches to augment manual efforts on improving the truthfulness and trustworthiness of online communications.
      • The inaugural Truth and Trust Online conference will be taking place on October 4th and 5th 2019 at BMA House in London.

        Key Dates

        • First call for papers: 2nd of April, 2019 *

        • Deadline for all submissions: 3rd of June, 2019
        • Notification of acceptance: Early July
        • Registration opens: End of June
        • Conference: 4th and 5th of October, 2019, BMA House, London, UK
    • From On Being with Pádraig Ó Tuama, about belonging gone bad and the scale of sectarianism: demonic
    • Fooling automated surveillance cameras: adversarial patches to attack person detection
      • Adversarial attacks on machine learning models have seen increasing interest in the past years. By making only subtle changes to the input of a convolutional neural network, the output of the network can be swayed to output a completely different result. The first attacks did this by changing pixel values of an input image slightly to fool a classifier to output the wrong class. Other approaches have tried to learn “patches” that can be applied to an object to fool detectors and classifiers. Some of these approaches have also shown that these attacks are feasible in the real-world, i.e. by modifying an object and filming it with a video camera. However, all of these approaches target classes that contain almost no intra-class variety (e.g. stop signs). The known structure of the object is then used to generate an adversarial patch on top of it. 
      • In this paper, we present an approach to generate adversarial patches to targets with lots of intra-class variety, namely persons. The goal is to generate a patch that is able successfully hide a person from a person detector. An attack that could for instance be used maliciously to circumvent surveillance systems, intruders can sneak around undetected by holding a small cardboard plate in front of their body aimed towards the surveillance camera. From our results we can see that our system is able significantly lower the accuracy of a person detector. Our approach also functions well in real-life scenarios where the patch is filmed by a camera. To the best of our knowledge we are the first to attempt this kind of attack on targets with a high level of intra-class variety like persons.
    • More adding Wayne’s notes into JASS paper. Figured out how to make something that looks like blockquotes without screwing up the JASS formatting:
      	\textit{"Get him home.  And deliver my cut of earnings to the people of Phandalin near Neverwinter, my home". With this, before anyone can stop him, Edmund turns to the dragon. "I make a counter offer.  In exchange for them motions to the two caged people. I offer myself to take their place.  I will remain.  I will starve.  You will lose two peasants, and in return you will gain all that I have to offer.  Edmund of house DeVir of Neverwinter.  The last of a noble bloodline of the ruling class."} - Edmond: Group 2
    • More Machine Teaching paper


Phil 4.15.19

7:00 – ASRC TL

  • I’ve been hunting around for what a core message of the iSchool should be (And I like LAMDA), but I think this sums it up nicely. From The Library Book: Library
  • use arxiv2bibtex to get bibtex information for arXiv submissions for use in BibTeX, on web pages or in Wikis. You can enter:
    • one or several paper IDs like “1510.01797” or “math/0506203”.
    • your arXiv author ID looking similar to “grafvbothmer_h_1” to get a list of all your submitted papers.
    • your ORCID ID looking similar to “0000-0003-0136-444X” which you should register with your arXiv-account.
  • Here’s hoping the proposal goes in. It did!
  • Start on IEEE paper? Nope. Did get back to Grokking Deep learning. Trying to get the system working with MNIST.
  • Something for the arousal potential/Clockwork Muse file: Accelerating dynamics of collective attention
    • With news pushed to smart phones in real time and social media reactions spreading across the globe in seconds, the public discussion can appear accelerated and temporally fragmented. In longitudinal datasets across various domains, covering multiple decades, we find increasing gradients and shortened periods in the trajectories of how cultural items receive collective attention. Is this the inevitable conclusion of the way information is disseminated and consumed? Our findings support this hypothesis. Using a simple mathematical model of topics competing for finite collective attention, we are able to explain the empirical data remarkably well. Our modeling suggests that the accelerating ups and downs of popular content are driven by increasing production and consumption of content, resulting in a more rapid exhaustion of limited attention resources. In the interplay with competition for novelty, this causes growing turnover rates and individual topics receiving shorter intervals of collective attention.
  • Chasing down narrative embedding using force-directed graphs and found Tulip
    • Tulip is an information visualization framework dedicated to the analysis and visualization of relational data. Tulip aims to provide the developer with a complete library, supporting the design of interactive information visualization applications for relational data that can be tailored to the problems he or she is addressing.
    • There are Python bindings. The following are for large layouts
      • FM^3 (OGDF)
        • Implements the FM³ layout algorithm by Hachul and Jünger. It is a multilevel, force-directed layout algorithm that can be applied to very large graphs.
      • H3 (GRIP)
        • Implements the H3 layout technique for drawing large directed graphs as node-link diagrams in 3D hyperbolic space. That algorithm can lay out much larger structures than can be handled using traditional techniques for drawing general graphs because it assumes a hierarchical nature of the data. It was first published as: H3: Laying out Large Directed Graphs in 3D Hyperbolic Space . Tamara Munzner. Proceedings of the 1997 IEEE Symposium on Information Visualization, Phoenix, AZ, pp 2-10, 1997. The implementation in Python (MIT License) has been written by BuzzFeed (
  • Mahzarin R. Banaji
    • Professor Banaji studies thinking and feeling as they unfold in social context, with a focus on mental systems that operate in implicit or unconscious mode. She studies social attitudes and beliefs in adults and children, especially those that have roots in group membership.  She explores the implications of her work for questions of individual responsibility and social justice in democratic societies. Her current research interests focus on the origins of social cognition and applications of implicit cognition to improve individual decisions and organizational policies. 
      • What do Different Beliefs Tell us? An Examination of Factual, Opinion-Based, and Religious Beliefs 
        • Children and adults differentiate statements of religious belief from statements of fact and opinion, but the basis of that differentiation remains unclear. Across three experiments, adults and 8-10-year-old children heard statements of factual, opinion-based, and religious belief. Adults and children judged that statements of factual belief revealed more about the world, statements of opinion revealed more about individuals, and statements of religious belief provided information about both. Children—unlike adults—judged that statements of religious belief revealed more about the world than the believer. These results led to three conclusions. First, judgments concerning the relative amount of information statements of religious belief provide about individuals change across development, perhaps because adults have more experience with diversity. Second, recognizing that statements of religious belief provide information about both the world and the believer does not require protracted learning. Third, statements of religious belief are interpreted as amalgams of factual and opinion-based statements.
          • My sense is that these three regios – factual, religious, and opinion are huge attractors in our belief landscape
      • Studying Implicit Social Cognition with Noninvasive Brain Stimulation

Phil 4.14.19

An interesting take on diversity science that I had never heard of:


UnTangle Map: Visual Analysis of Probabilistic Multi-Label Data

  • Data with multiple probabilistic labels are common in many situations. For example, a movie may be associated with multiple genres with different levels of confidence. Despite their ubiquity, the problem of visualizing probabilistic labels has not been adequately addressed. Existing approaches often either discard the probabilistic information, or map the data to a low-dimensional subspace where their associations with original labels are obscured. In this paper, we propose a novel visual technique, UnTangle Map, for visualizing probabilistic multi-labels. In our proposed visualization, data items are placed inside a web of connected triangles, with labels assigned to the triangle vertices such that nearby labels are more relevant to each other. The positions of the data items are determined based on the probabilistic associations between items and labels. UnTangle Map provides both (a) an automatic label placement algorithm, and (b) adaptive interactions that allow users to control the label positioning for different information needs. Our work makes a unique contribution by providing an effective way to investigate the relationship between data items and their probabilistic labels, as well as the relationships among labels. Our user study suggests that the visualization effectively helps users discover emergent patterns and compare the nuances of probabilistic information in the data labels. untangle

Spring Embedders and Force Directed Graph Drawing Algorithms

  • Force-directed algorithms are among the most flexible methods for calculating layouts of simple undirected graphs. Also known as spring embedders, such algorithms calculate the layout of a graph using only information contained within the structure of the graph itself, rather than relying on domain-specific knowledge. Graphs drawn with these algorithms tend to be aesthetically pleasing, exhibit symmetries, and tend to produce crossing-free layouts for planar graphs. In this survey we consider several classical algorithms, starting from Tutte’s 1963 barycentric method, and including recent scalable multiscale methods for large and dynamic graphs. spring

Phil 4.12.19

9:00 – 5:00 ASRC TL

  • Finished the BAA white paper(?), and asked for hours to write the full paper for the Symposium on Technologies for Homeland Security
  • These are appropriate:
    • Meaningful Human Control over Autonomous Systems: A Philosophical Account
      • In this paper, we provide an analysis of the sort of control humans need to have over (semi)autonomous systems such that unreasonable risks are avoided, that human responsibility will not evaporate, and that is there is a place to turn to in case of untoward outcomes. We argue that higher levels of autonomy of systems can and should be combined with human control and responsibility. We apply the notion of guidance control that has been developed by Fischer and Ravizza (1998) in the philosophical debate about moral responsibility and free will, and we adapt it as to cover actions mediated by the use of (semi)autonomous robotic systems. As we will show, this analysis can be fruitfully applied in the context of autonomous weapon systems as well as of autonomous systems more generally. We think we herewith provide a first full-fledged philosophical account of “meaningful human control over autonomous systems.”
    • The following is the preprint PDF of our paper on driver functional vigilance during Tesla Autopilot assisted driving: Human Side of Tesla Autopilot: Exploration of Functional Vigilance in Real-World Human-Machine Collaboration. It is part of the MIT-AVT large-scale naturalistic driving study
    • What I Learned from a Year of ChinAI
      • Finally, Chinese thinkers are engaged on broader issues of AI ethics, including the risks of human-level machine intelligence and beyond. Zhao Tingyang, an influential philosopher at the Chinese Academy of Social Sciences, has written a long essay on near-term and long-term AI safety issues, including the prospect of superintelligence. Professor Zhihua Zhou, who leads an impressive lab at Nanjing University, argued in an article for the China Computer Federation that even if strong AI is possible, it is something that AI researchers should stay away from.
  • And so ends a long, hectic, but satisfying week.

Phil 4.6.19

Added a section on calculating belief terms in the trap room. And then worked on the paper for the rest of the day. It’s currently 7:45, and the first draft is DONE!

Sent drafts off to Wayne

Working on the lit review. Reading Foucault’s Of Other Spaces:

  • We are in the epoch of simultaneity: we are in the epoch of juxtaposition, the epoch of the near and far, of the side-by-side, of the dispersed. We are at a moment, I believe, when our experience of the world is less that of a long life developing through time than that of a network that connects points and intersects with its own skein. (Page 22)
  • Today the site has been substituted for extension which itself had replaced emplacement. The site is defined by relations of proximity between points or elements; formally, we can describe these relations as series, trees, or grids (Page 23)
  • …we do not live in a homogeneous and empty space, but on the contrary in a space thoroughly imbued with quantities and perhaps thoroughly fantasmatic as well. The space of our primary perception, the space of our dreams and that of our passions hold within themselves qualities that seem intrinsic: there is a light, ethereal, transparent space, or again a dark, rough, encumbered space; a space from above, of summits, or on the contrary a space from below, of mud; or again a space that can be flowing like sparkling water, or a space that is fixed, congealed, like stone or crystal. (Page 23)
  • Places of this kind are outside of all places, even though it may be possible to indicate their location in reality. Because these places are absolutely different from all the sites that they reflect and speak about, I shall call them, by way of contrast to utopias, heterotopias. I believe that between utopias and these quite other sites, these heterotopias, there might be a sort of mixed, joint experience, which would be the mirror (Page 24)
  • the study, analysis, description, and “reading” (as some like to say nowadays) of these different spaces, of these other places. As a sort of simultaneously mythic and real contestation of the space in which we live, this description could be called heterotopology (Page 24)
  • But these heterotopias of crisis are disappearing today and are being replaced, I believe, by what we might call heterotopias of deviation: those in which individuals whose behavior is deviant in re 1:ition to the required mean or norm are placed. Cases of this are rest homes and psychiatric hospitals, and of course prisons; and one should perhaps add retirement homes that are, as it were, on the borderline between the heterotopia of crisis and the heterotopia of deviation since, after all, old age is a crisis, but is also a deviation since, in our society where leisure is the rule, idleness is a sort of deviation. (Page 25)
  • Third principle. The heterotopia is capable of juxtaposing in a single real place several spaces, several sites that are in themselves incompatible. Thus it is that the theater brings onto the rectangle of the stage, one after the other, a whole series of places that are foreign to one another; thus it is that the cinema is a very odd rectangular room, at the end of which, on a two-dimensional screen, one sees the projection of a three-dimensional space; but perhaps the oldest example of these heterotopias that take the form of contradictory sites is the garden. We must not forget that in the Orient the garden, an astonishing creation that is now a thousand years old, had very deep and seemingly superimposed meanings. (Page 25)
  • Fourth principle. Heterotopias are most often linked to slices in time-which is to say that they open onto what might be termed, for the sake of symmetry, heterochronies. (page 26)
  • Fifth principle. Heterotopias always presuppose a system of opening and closing that both isolates them and makes them penetrable. In general, the heterotopic site is not freely accessible like a public place. Either the entry is compulsory, as in the case of entering a barracks or a prison, or else the individual has to submit to rites and purifications. To get in one must have a certain permission and make certain gestures. (Page 26)
    • This limitation is why it is possible to come to consensus in reasonable timeframes
  • The last trait of heterotopias is that they have a function in relation to all the space that remains. This function unfolds between two extreme poles. Either their role is to create a space of illusion that exposes every real space, all the sites inside of which human life is partitioned, as still more illusory (perhaps that is the role that was played by those famous brothels of which we are now deprived). Or else, on the contrary, their role is to create a space that is other, another real space, as perfect, as meticulous, as well arranged as ours is messy, ill constructed, and jumbled. This latter type would be the heterotopia, not of illusion, but of compensation (Page 27)
  • The ship is the heterotopia par excellence. In civilizations without boats, dreams dry up, espionage takes the place of adventure, and the police take the place of pirates. (Page 27)

Foucault’s Heterotopias as Play Spaces

  • Tim Hutchings – Western Oregon University
  • Jason Giardino – Games to Gather
  • However, if the game was set on the deck of an aircraft carrier, we might find Foucault better abled to address the significance of that setting through his interest in social and architectural spaces. A Magic Circle is created when players ‘other’ themselves for the purpose of a game, a heterotopia is created when ‘others’ find a space within a larger structure in order to engage their othered selves. (page 12)
    • We are using games to map structuctures in larger spaces
  • “Heterotopias have a specific function that is a reflection of the society in which they exist.” (Page 12)
  • A heterotopia exists within a larger architectural and social space but is apart from it. However, a heterotopia operates in reaction to this larger framework – it considers the world from the margins and found spaces between the controls and intentions of society as a whole. Dungeons & Dragons remains blissfully ignorant of the space which hosts it. (Page 12)
    • Our aim of using these collective and repeated actions to produce maps of both place and space, when combined with aspects such as the explicit acceptance of the IRB meet this requirement, I think.



Phil 3.22.19

7:00 – 5:30 ASRC PhD

  • Morning thought – primordial movement is navigation at a more generalized level. At this level, only broad features are visible, so it’s only easy to jump to a large, common feature like fear-of-the-other. For humans, I think there are very few accessible features at this level.
  • Adversarial attacks on medical machine learning
    • With public and academic attention increasingly focused on the new role of machine learning in the health information economy, an unusual and no-longer-esoteric category of vulnerabilities in machine-learning systems could prove important. These vulnerabilities allow a small, carefully designed change in how inputs are presented to a system to completely alter its output, causing it to confidently arrive at manifestly wrong conclusions. These advanced techniques to subvert otherwise-reliable machine-learning systems—so-called adversarial attacks—have, to date, been of interest primarily to computer science researchers (1). However, the landscape of often-competing interests within health care, and billions of dollars at stake in systems’ outputs, implies considerable problems. We outline motivations that various players in the health care system may have to use adversarial attacks and begin a discussion of what to do about them. Far from discouraging continued innovation with medical machine learning, we call for active engagement of medical, technical, legal, and ethical experts in pursuit of efficient, broadly available, and effective health care that machine learning will enable.
  • Jumping straight into coding
    • Moved the menu bars around
      • Added a “Chains” menu that runs sequences of analytics
      • Added an NLP menu for BOW and TF-IDF
      • Working on parsing the selected listings to add to the various lists
      • Added a “search” button to search for neighbors of terms in the spaces and places text areas
      • Ran into a problem when I was calculating TF-IDF From here, but the way to get the data is here, spoilers – it uses Dataframes. Anyway, artifacts from Slack and PHPBB we interfering with the analytics. Things like [i:3fsgwhpz]. So I added a lot of preprocessing. First, more regexes:
        punctuation_regex = re.compile(r"[\",\-\_\.\d+?!*;“”]")
        bracket_regex = re.compile(r"\[.*?\]")
        amper_semicolon_regex = re.compile(r"\&.*?\;")

        And then some word-by-word testing and more regexing:

        def cleanup_text(self, raw: str) -> str:
            raw = self.bracket_regex.sub("",raw)
            raw = self.amper_semicolon_regex.sub("",raw)
            words = raw.split(" ")
            s = ""
            for word in words:
                if len(word) < 20:
                    word = self.punctuation_regex.sub("",word)
                    word = word.strip()
                    word = word.lower()
                    s += " {}".format(word)
                    print("Threw out {}".format(word))
            return s
      • Anyway, the results are pretty good now with TF-IDF. Here’s the top few terms for each player’s runs
        post TF-IDF
        	javelin: 1.3235824005932413
        	orc: 1.2596337832554234
        	don: 1.2329356851106978
        	mindy: 1.1935877563453061
        	dragon: 1.180695872064165
        	room: 1.16758789676671
        	goblin: 1.1244271157713812
        	gate: 1.0518778198496626
        	muttered: 0.9602704217082824
        	orb: 0.7818369426232508
        	vines: 0.7682713289173773
        	around: 0.7650741399517217
        	believe: 0.7181160263645541
        	set: 0.6960723252519683
        post TF-IDF
        	troll: 1.8877816896391235
        	room: 1.6145159552006425
        	spell: 1.19387373804735
        	orb: 1.031131725198719
        	hand: 1.0226191383574903
        	halfling: 0.882770501608177
        	feather: 0.8321564150194518
        	chest: 0.7956715550842
        	need: 0.7833254070966856
        	without: 0.7774257667568547
        	thought: 0.7698168337310007
        	wasn: 0.7681132279117597
        	grogg: 0.7397095370527041
        	nodded: 0.7283692418929164
        	cricket: 0.7152753845274986
        post TF-IDF
        	room: 1.37664885493529
        	halfling: 1.3095258648568422
        	orb: 1.1635393833341
        	arrow: 1.0958743699311024
        	bow: 1.0833323871838676
        	woman: 0.905661830111989
        	sword: 0.8274886204621582
        	side: 0.8159855961191507
        	door: 0.8030328480633289
        	weapons: 0.8023256227742956
        	bit: 0.7654054685520582
        	armor: 0.6925203949859854
        	compatriots: 0.6877982251257945
        	moment: 0.666106887452693
        	ready: 0.6591955622573524
        	wasn: 0.6407825783880001
        	group: 0.6181005287618395
        	words: 0.6162132133458346
        	statues: 0.6129058701485565
        post TF-IDF
        	grogg: 5.334199523123002
        	room: 3.811509447108922
        	gate: 3.258183021914178
        	orb: 2.618164708893951
        	troll: 2.613186928575063
        	arrow: 2.324879853387413
        	looking: 2.0945608918805405
        	dragon: 2.0386853821484214
        	statues: 2.0307941282615394
        	halfling: 1.9946267677568987
        	goblin: 1.9479046173471883
        	eyes: 1.9250729565572604
        	large: 1.8740265406115013
        	hand: 1.8621985701316857
        	ooc: 1.854167610118333
        	orc: 1.8453651951258079
        Aaron Buchanan-player:
        post TF-IDF
        	smile: 5.028089150947501
        	troll: 4.349229589605341
        	linda: 4.01623419920215
        	damage: 3.5816072459387898
        	let: 3.145522725372224
        	know: 3.0568701804539486
        	jenni: 3.0150241755107605
        	need: 2.9865597817204916
        	don: 2.89736685000583
        	fire: 2.8533063572331154
        	hit: 2.750325190292788
        	elf: 2.61638151392588
        	nothing: 2.5832965974665827
        	rope: 2.5651899037822403
        	want: 2.5516172618521207
        	room: 2.5234046485126127
        	hand: 2.408589994530533
        	key: 2.400913929253641
        	halfling: 2.300372097141645
        	grogg: 2.2976898742276277
        post TF-IDF
        	insight: 3.5333368131417924
        	troll: 3.4738014944618905
        	help: 2.629726435567097
        	grogg: 2.396996336469604
        	need: 2.358944535917952
        	room: 2.25768912386651
        	healing: 2.2382624097615995
        	rolls: 2.2229326490531314
        	gate: 2.195439698041948
        	around: 2.161868029714761
        	flame: 2.132641891485049
        	perception: 2.1149040159363293
        	floor: 2.1054598538974045
        	hands: 1.9310855224062018
        	light: 1.8784320905937355
        	uses: 1.850257078968512
        	catch: 1.793277658871867
        Bjorn Hasseler-player:
        post TF-IDF
        	flame: 2.315315586844817
        	sacred: 2.315315586844817
        	stonecunning: 2.1557147060826947
        	rolls: 2.132883047459771
        	grogg: 1.9660626127710805
        	don: 1.9424906312537291
        	steps: 1.935482241603244
        	bridge: 1.7092785394164918
        	rope: 1.5744166673302291
        	torches: 1.551554596214274
        	stairs: 1.4732750153279608
        	platform: 1.3689503773093064
        	vines: 1.3351891642736244
        	light: 1.3217202403569526
        post TF-IDF
        	troll: 5.780387270246775
        	grogg: 4.59954530049338
        	need: 4.379175783748707
        	attack: 3.7429397050152247
        	don: 3.564218421074024
        	open: 3.503242156009218
        	gate: 3.3068573706012985
        	stealth: 3.1899559813180645
        	traps: 2.965951521209904
        	chest: 2.9426150667239175
        	side: 2.8272991421295277
        	room: 2.8187225708944883
        	dragon: 2.7919898167411095
        	party: 2.784297298562819
        	know: 2.698287503059542
        post TF-IDF
        	grogg: 10.15480371661793
        	damage: 6.745957190399183
        	gate: 4.595526542550383
        	turn: 4.47763106887882
        	side: 4.220054751334396
        	room: 4.0759304935283875
        	troll: 3.6496283755351433
        	persuasion: 3.427787051079431
        	stairs: 3.2452878097049718
        	open: 3.0691978408049714
        	appears: 2.9662151644031236
        	barrier: 2.9526976397873197
        	hit: 2.882801312489094
        	please: 2.756473252393314
        	feet: 2.7553337830423685
        post TF-IDF
        	rope: 2.5925740290266477
        	troll: 2.149767946611558
        	grogg: 2.1373623910153023
        	close: 2.093606121380299
        	goes: 1.9114083131138986
        	thing: 1.879425660287383
        	gate: 1.8498993377390152
        	behind: 1.7759591324283694
        	around: 1.7739744768952832
        	eyes: 1.6015525983573213
        	along: 1.565130385605012
        	face: 1.5465277621378841
        	merric: 1.531838768719999
        	goblin: 1.5017357357398398
        	chest: 1.4793322265307385
        post TF-IDF
        	rope: 2.5574727497157186
        	bit: 2.334695846271241
        	halfling: 2.2917865866720875
        	turn: 2.2913671375617244
        	help: 2.263326099701241
        	want: 2.255517431033907
        	let: 2.2248419816867973
        	hand: 2.05823145874274
        	thing: 2.0252535914010243
        	need: 2.017853031957051
        	trying: 1.9392838304479607
        	won: 1.9074029011042937
        	lever: 1.8940047810992084
        	motions: 1.8791666280630153
        	grogg: 1.8512620533629853
        	know: 1.8460073095362568
        post TF-IDF
        	joy: 2.2090099096592093
        	bow: 1.4708821850714477
        	comrades: 1.3450198066079633
        	agreed: 1.2909672047219294
        	shit: 1.2511351948636689
        	hand: 1.1939893091569087
        	simply: 1.0754065506075219
        	alongside: 1.03095098597318
        	ready: 1.030909228527731
        	moves: 1.0217451884953292
        	follows: 1.019308558744064
        	esvele: 1.0031051305561383
        	eyes: 1.0031051305561383
        	alrighty: 1.0
        	sounds: 1.0
        	wow: 1.0
        	armor: 0.9675296552629622
        	goblin: 0.9675296552629622
        	arrow: 0.959551586099932
        post TF-IDF
        	grogg: 9.574956839446978
        	room: 7.7929146794417985
        	gate: 7.769157727681967
        	open: 5.161416388301517
        	side: 4.9552473292407315
        	hand: 4.920538249739186
        	something: 4.862660052617354
        	troll: 4.756897094197843
        	damage: 4.698981284560832
        	phoenix: 4.506875041306749
        	group: 4.4419312361884575
        	stealth: 4.347602688687722
        	bee: 4.337563548710324
        	stairs: 4.272837824041584
        	perception: 4.240823300482532
        	investigation: 4.214126267526979
        	bit: 4.2116435909201435
        	goblin: 4.16370490562877
        post TF-IDF
        	gate: 3.813331273921538
        	course: 3.3238613690720182
        	light: 3.2357123635315
        	yenadar: 3.206131400462222
        	move: 3.0410330090181983
        	orc: 2.920652421803098
        	dragon: 2.91393405622444
        	casts: 2.910174915050543
        	shelton: 2.781316206653326
        	turn: 2.7696197904765247
        	close: 2.7395876537286137
        	history: 2.7290686528241705
        	rope: 2.533647571484718
        	toss: 2.488833414797614
        post TF-IDF
        	rope: 7.346484814122864
        	mage: 5.1901641703849695
        	hand: 5.169823617707603
        	something: 4.052962289815423
        	room: 3.7977359903069874
        	spell: 3.733564719352958
        	feet: 3.629297463463484
        	gate: 3.4221850444525543
        	need: 3.313446574887807
        	hands: 3.306280386619182
        	casts: 3.239250407373651
        	arrows: 3.094136824719543
        	hahaha: 3.0
        	lorelai: 2.8832894462350955
        	troll: 2.879950620848435
        post TF-IDF
        	javelin: 5.50125987652874
        	sigh: 4.0
        	hmm: 3.534360458898429
        	room: 3.5148283185111264
        	yup: 3.5117826563035313
        	axe: 3.114116974088525
        	wait: 3.0448104923325108
        	course: 2.7955498582374037
        	chest: 2.7578668995086213
        	kk: 2.68753920352695
        	rope: 2.491724054450192
        	hand: 2.409513756019609
        	attack: 2.380401354039185
        	side: 2.2585165820164
        	ft: 2.2506235321034813
        	lead: 2.229579193706388
        	better: 2.2144928823627117
        	move: 2.159570674311593
        	troll: 2.149851721830461
        Shelton Herrington-player:
        post TF-IDF
        	hehe: 12.124909531389427
        	don: 11.505547928323026
        	guess: 10.67778790195941
        	nice: 9.170367618719803
        	rope: 8.698156248650768
        	orb: 8.567297721201122
        	hey: 8.3986603737825
        	hmm: 8.284208790999351
        	guys: 8.195019661596476
        	want: 7.965528793382409
        	door: 7.900199902653034
        	know: 7.817490225187236
        	can: 6.476312939358579
        	maybe: 6.393688899561484
        	around: 6.370346146839613