Category Archives: proposals

Phil 3.4.19

7:00 – 5:00 ASRC

  • Build an interactive SequenceAnalyzer. The adjustments are
    • Number of buckets
    • Percentages for each analytic (percentages to keep/discard
    • Selectable skip words that can be added to a list (in the db?)
  • Algorithm
    1. Find the most common words across all groups, these are skip_words
    2. Find the most common words along the entire series of posts per player and eliminate them
    3. Find the most common/central words across all sequences and keep those as belief places
    4. For each sequence by group, find the most common/central words after the belief places. These are the belief spaces.
    5. Build an adjacency matrix of players, groups, places and spaces
    6. Build submatrices for centrality calculations? This could be rather than finding the most common
    7. Possible word2vec variations?
      1. It seems to me that I might be able to use direction cosines and dynamic time warping to calculate the similarity of posts and align them better than the overall scaling that I’m doing now. DM posts introducing a room should align perfectly, and then other scaling could happen between those areas of greatest alignment
  • Display
    • Menu:
      • Save spreadsheet (includes config, included words, posts(?), trajectories)
      • load data
      • select database
      • select group within db
      • load/save config file
      • clear all
    • Fields
      • percent for A1, A2, A3, A4
      • Centrality/Sum switch
      • BOW/TF-IDF switch
      • Word2vec switch?
    • Textarea (areas? tabbed?)
      • Table with rows as sequence step. Columns are grouped by places, spaces, groups, and players
    • Work on Antonio’s paper got a first draft on introduction and motivation
    • BAA
      • Upload latex and references to laptop
    • Haircut! Pack!
    • Model-Based Reinforcement Learning for Atari
      • Model-free reinforcement learning (RL) can be used to learn effective policies for complex tasks, such as Atari games, even from image observations. However, this typically requires very large amounts of interaction — substantially more, in fact, than a human would need to learn the same games. How can people learn so quickly? Part of the answer may be that people can learn how the game works and predict which actions will lead to desirable outcomes. In this paper, we explore how video prediction models can similarly enable agents to solve Atari games with orders of magnitude fewer interactions than model-free methods. We describe Simulated Policy Learning (SimPLe), a complete model-based deep RL algorithm based on video prediction models and present a comparison of several model architectures, including a novel architecture that yields the best results in our setting. Our experiments evaluate SimPLe on a range of Atari games and achieve competitive results with only 100K interactions between the agent and the environment (400K frames), which corresponds to about two hours of real-time play.

 

Phil 2.6.19

7:00 – 5:00 ASRC IRAD (TL)

  • The role of maps in spatial knowledge acquisition
    • The Cartographic Journal
    • One goal of cartographic research is to improve the usefulness of maps. To do so, we must consider the process of spatial knowledge acquisition, the role of maps in that process, and the content of cognitive representations derived. Research from psychology, geography, and other disciplines related to these issues is reviewed. This review is used to suggest potential new directions for research with particular attention to spatial problem solving and geographic instruction. A classroom experiment related to these issues is then described. The experiment highlights some of the implications that a concern for the process of spatial knowledge acquisition will have on questions and methods of cartographic research as well as on the use of maps in geographic instruction. It also provides evidence of independent but interrelated verbal and spatial components of regional images that can be altered by directed map work.
  • It’s Not A Lie If You Believe It: Lying and Belief Distortion Under Norm-Uncertainty
    • This paper focuses on norm-following considerations as motivating behavior when lying opportunities are present. To obtain evidence on what makes it harder/easier to lie, we hypothesize that subjects might use belief-manipulation in order to justify their lying. We employ a two-stage variant of a cheating paradigm, in which subjects’ beliefs are elicited in stage 1 before performing the die task in stage 2. In stage 1: a) we elicit the subjects’ beliefs about majoritarian (i) behavior or (ii) normative beliefs in a previous session, and b) we vary whether participants are (i) aware or (ii) unaware of the upcoming opportunity to lie. We show that belief manipulation happens, and takes the form of people convincing themselves that lying behavior is widespread. In contrast with beliefs about the behavior of others, we find that beliefs about their normative convictions are not distorted, since believing that the majority disapproves of lying does not inhibit own lying. These findings are consistent with a model where agents are motivated by norm-following concerns, and honest behavior is a strong indicator of disapproval of lying but disapproval of lying is not a strong indicator of honest behavior. We provide evidence that supports this hypothesis.
  • Sent a note to Slack, asking for an academic plan. They do, and there are forms to fill out. I need to send Don some text that he can send back to me on letterhead.
  • Looks like I’m not going to the TF Dev Conf this year…
  • Continuing with the INSERT code
  • Meeting in Greenbelt to discuss… what, exactly?
  • Got a cool book: A Programmer’s Introduction to Mathematics
  • Got my converter creating error-free sql! t_user
  • Working on reading channel data into the db. Possibly done, but I’m afraid to run it so late in the day. I have chores!
  • Reviewing proposal for missing citations – done

Phil 2.5.19

7:00 – 5:00 ASRC IRAD

  • Got the parser to the point that it’s creating query strings, but I need to escape the text properly
  • Created and ab_slack mysql db
  • Added “parent_id” and an auto increment ID to any of the arrays that are associated with the Slack data
  • Reviewing sections 1-3 – done
  • Figure out some past performance – done
  • Work on the CV. Add the GF work and A2P ML work. – done
  • Start reimbursement for NJ trip
  •  Accidentally managed to start a $45/month subscription to the IEEE digital library. It really reeks of deceptive practices. There is nothing on the subscription page that informs you that this is a $45/month, 6-month minimum purchase. I’m about to contact the Maryland deceptive practices people to see if there is legal action that can be brought

Phil 1.22.19

9:00 – 5:00 – ASRC PhD/NASA

  • Google AI proposal is due today! DONE!
  • Next steps for financial analytics
    • Get the historical data to Aaron’s code. Need to look at Pandas’ read_json
    • Get the predictions and intervals back
    • Store the raw data
    • update and insert the lineitems – nope
    • populate PredictedAvailableUDO table
  • Big five personality test (For players and characters) Github

Phil 1.17.19

7:00 – 3:30 ASRC PhD, NASA

  • Lyrn.AI – Deep Learning Explained
  • Re-learning how to code in PHP again, which is easier if you’ve been doing a lot of C++/Java and not so much if you’ve been doing Python. Anyway, I wrote a small class:
    class DbIO2 {
        protected $connection = NULL;
    
        function connect($db_hostname, $db_username, $db_password, $db_database){
            $toReturn = array();
            $this->connection = new mysqli($db_hostname, $db_username, $db_password, $db_database);
            if($this->connection->connect_error){
                $toReturn['connect_successful'] = false;
                $toReturn['connect_error'] = $this->connection->error;
            } else {
                $toReturn['connect_successful'] = true;
            }
            return $toReturn;
        }
    
    
        function runQuery($query) {
            $toReturn = array();
            if($query == null){
                $toReturn['query_error'] = "query is empty";
                return $toReturn;
            }
            $result = $this->connection->query($query);
    
            if (!$result) {
                $toReturn['database_access'] = $this->connection->error;
                return $toReturn;
            }
    
            $numRows = $result->num_rows;
    
            for ($j = 0 ; $j < $numRows ; ++$j)         {             $result->data_seek($j);
                $row = $result->fetch_assoc();
                $toReturn[$j] = $row;
            }
            return $toReturn;
        }
    }
  • And exercised it
    require_once '../../phpFiles/ro_login.php';
    require_once '../libs/io2.php';
    
    $dbio = new DbIO2();
    
    $result = $dbio->connect($db_hostname, $db_username, $db_password, $db_database);
    
    printf ("%s\n",json_encode($result));
    
    $result = $dbio->runQuery("select * from post_view");
    
    foreach ($result as $row)
        printf ("%s\n", json_encode($row));
  • Which gave me some results
    {"connect_successful":true}
    {"post_id":"4","post_time":"2018-11-27 16:00:27","topic_id":"4","topic_title":"SUBJECT: 3 Room Linear Dungeon Test 1","forum_id":"14","forum_name":"DB Test","username":"dungeon_master1","poster_ip":"71.244.249.217","post_subject":"SUBJECT: 3 Room Linear Dungeon Test 1","post_text":"POST: dungeon_master1 says that you are about to take on a 3-room linear dungeon."}
    {"post_id":"5","post_time":"2018-11-27 16:09:12","topic_id":"4","topic_title":"SUBJECT: 3 Room Linear Dungeon Test 1","forum_id":"14","forum_name":"DB Test","username":"dungeon_master1","poster_ip":"71.244.249.217","post_subject":"SUBJECT: dungeon_master1's introduction to room_0","post_text":"POST: dungeon_master1 says, The party now finds itself in room_0. There is a troll here."}
    (repeat for another 200+ lines)
  • So I’m well on my way to being able to show the stories (both from the phpbb and slack) on the Antibubbles “stories” page

4:00 – 5:00 Meeting with Don

Phil 12.28.18

7:00 – 4:30 ASRC NASA

  • Human mind excels at quantum-physics computer game 3o6ozkvdtdarNDhGEw
  • Continuing on the proposal:
    • [Optional] What are your success metrics for the AI system (i.e., how will you know whether the system has succeeded or failed)?
      • Discuss the spectrum of success, from classification of behavior type by syntax patterns (LSTM) to human-based manifold learning (t-sne, xxx2vec, etc) for map generation, to development of new spatial neural frameworks, potentially based on grid neurons.
    • [Optional] What else we should know?
      • I want to say something about how this is based on animal studies, and how the idea of intelligence being expensive computation has to affect any kind of collective system. Still thinking about that.
      • Also, the economic power of maps, as discussed here
    • How will you sustain and grow the impact of this work beyond this grant? How could your project and its impact grow beyond what you’ve proposed in this application?
    • Need to add a brief description of each paper and include the venue and a link

Phil 12.27.18

7:00 – 11:00 PhD

  • How Much of the Internet Is Fake? Turns Out, a Lot of It, Actually.
    • Fake people with fake cookies and fake social-media accounts, fake-moving their fake cursors, fake-clicking on fake websites — the fraudsters had essentially created a simulacrum of the internet, where the only real things were the ads.
  • More proposal. With respect to bot traffic, there is standalone, monolithic and complex behaviors that can also be tracked and used to assess the underlying information. Adversarial herding is an example.
  • Ran out of steam. Hung up on these questions:
    • [Optional] What are your success metrics for the AI system (i.e., how will you know whether the system has succeeded or failed)?
      • Discuss the spectrum of success, from classification of behavior type by syntax patterns (LSTM) to human-based manifold learning (t-sne, xxx2vec, etc) for map generation, to development of new spatial neural frameworks, potentially based on grid neurons.
    • [Optional] What else we should know?
      • I want to say something about how this is based on animal studies, and how the idea of intelligence being expensive computation has to affect any kind of collective system. Still thinking about that.
      • Also, the economic power of maps, as discussed here
    • How will you sustain and grow the impact of this work beyond this grant? How could your project and its impact grow beyond what you’ve proposed in this application?
    • Need to add a brief description of each paper and include the venue and a link

Phil 12.24.18

PhD 7:00 – 3:00

Phil 11.7.18

Let the House Subcommittee investigations begin! Also, better redistricting?

7:00 – 5:00 ASRC PhD/BD

  • Rather than Deep Learning with Keras, I’m starting on Grokking Deep Learning. I need better grounding
    • Installed Jupyter
  • After lunch, send follow-up emails to the technical POCs. This will be the basis for the white paper: Tentative findings/implications for design. Modify it on the blog page first and then use to create the LaTex doc. Make that one project, with different mains that share overlapping content.
  • Characterizing Online Public Discussions through Patterns of Participant Interactions
    • Public discussions on social media platforms are an intrinsic part of online information consumption. Characterizing the diverse range of discussions that can arise is crucial for these platforms, as they may seek to organize and curate them. This paper introduces a computational framework to characterize public discussions, relying on a representation that captures a broad set of social patterns which emerge from the interactions between interlocutors, comments and audience reactions. We apply our framework to study public discussions on Facebook at two complementary scales. First, we use it to predict the eventual trajectory of individual discussions, anticipating future antisocial actions (such as participants blocking each other) and forecasting a discussion’s growth. Second, we systematically analyze the variation of discussions across thousands of Facebook sub-communities, revealing subtle differences (and unexpected similarities) in how people interact when discussing online content. We further show that this variation is driven more by participant tendencies than by the content triggering these discussions.
  • More latent space flocking from Innovation Hub
    • You Share Everything With Your Bestie. Even Brain Waves.
      •  Scientists have found that the brains of close friends respond in remarkably similar ways as they view a series of short videos: the same ebbs and swells of attention and distraction, the same peaking of reward processing here, boredom alerts there. The neural response patterns evoked by the videos — on subjects as diverse as the dangers of college football, the behavior of water in outer space, and Liam Neeson trying his hand at improv comedy — proved so congruent among friends, compared to patterns seen among people who were not friends, that the researchers could predict the strength of two people’s social bond based on their brain scans alone.

    • Similar neural responses predict friendship
      • Human social networks are overwhelmingly homophilous: individuals tend to befriend others who are similar to them in terms of a range of physical attributes (e.g., age, gender). Do similarities among friends reflect deeper similarities in how we perceive, interpret, and respond to the world? To test whether friendship, and more generally, social network proximity, is associated with increased similarity of real-time mental responding, we used functional magnetic resonance imaging to scan subjects’ brains during free viewing of naturalistic movies. Here we show evidence for neural homophily: neural responses when viewing audiovisual movies are exceptionally similar among friends, and that similarity decreases with increasing distance in a real-world social network. These results suggest that we are exceptionally similar to our friends in how we perceive and respond to the world around us, which has implications for interpersonal influence and attraction.
    • Brain-to-Brain coupling: A mechanism for creating and sharing a social world
      • Cognition materializes in an interpersonal space. The emergence of complex behaviors requires the coordination of actions among individuals according to a shared set of rules. Despite the central role of other individuals in shaping our minds, most cognitive studies focus on processes that occur within a single individual. We call for a shift from a single-brain to a multi-brain frame of reference. We argue that in many cases the neural processes in one brain are coupled to the neural processes in another brain via the transmission of a signal through the environment. Brain-to-brain coupling constrains and simplifies the actions of each individual in a social network, leading to complex joint behaviors that could not have emerged in isolation.
  • Started reading Similar neural responses predict friendship

Phil 11.5.18

7:00- 4:30 ASRC PhD

  • Make integer generator by scaling and shifting the floating point generator to the desired values and then truncating. It would be fun to read in a token list and have the waveform be words
    • Done with the int waveform. This is an integer waveform of the function
      math.sin(xx)*math.sin(xx/2.0)*math.cos(xx/4.0)

      set on a range from 0 – 100:

    •  IntWaves
    • And here’s the unmodified floating-point version of the same function:
    • FloatWaves
    • Here’s the same function as words:
      #confg: {"function":math.sin(xx)*math.sin(xx/2.0)*math.cos(xx/4.0), "rows":100, "sequence_length":20, "step":1, "delta":0.4, "type":"floating_point"}
      routed, traps, thrashing, fifteen, ultimately, dealt, anyway, apprehensions, boats, job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, 
      traps, thrashing, fifteen, ultimately, dealt, anyway, apprehensions, boats, job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, 
      thrashing, fifteen, ultimately, dealt, anyway, apprehensions, boats, job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, 
      fifteen, ultimately, dealt, anyway, apprehensions, boats, job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, 
      ultimately, dealt, anyway, apprehensions, boats, job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, 
      dealt, anyway, apprehensions, boats, job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, 
      anyway, apprehensions, boats, job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', 
      apprehensions, boats, job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, 
      boats, job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, 
      job, descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, 
      descended, tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, 
      tongue, dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, 
      dripping, adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, 
      adoration, boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, 
      boats, routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, guarded, 
      routed, routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, guarded, tempers, 
      routed, strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, guarded, tempers, partnership, 
      strokes, cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, guarded, tempers, partnership, bare, 
      cheerful, charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, guarded, tempers, partnership, bare, count, 
      charleses, travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, guarded, tempers, partnership, bare, count, descended, 
      travellers, unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, guarded, tempers, partnership, bare, count, descended, dashed, 
      unsuspected, malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, guarded, tempers, partnership, bare, count, descended, dashed, ears, 
      malingerer, respect, aback, vair', wraith, bare, creek, descended, assortment, flashed, reputation, guarded, tempers, partnership, bare, count, descended, dashed, ears, q, 
      

       

  • Started LSTMs again, using this example using Alice in Wonderland
  • Aaron and T in all day discussions with Kevin about NASA/NOAA. Dropped in a few times. NASA is airgapped, but you can bring code in and out. Bringing code in requires a review.
  • Call the Army BAA people. We need white paper templates and a response for Dr. Palazzolo.
  • Finish and submit 810 reviews tonight. Done.
  • This is important for the DARPA and Army BAAs: The geographic embedding of online echo chambers: Evidence from the Brexit campaign
    • This study explores the geographic dependencies of echo-chamber communication on Twitter during the Brexit campaign. We review the evidence positing that online interactions lead to filter bubbles to test whether echo chambers are restricted to online patterns of interaction or are associated with physical, in-person interaction. We identify the location of users, estimate their partisan affiliation, and finally calculate the distance between sender and receiver of @-mentions and retweets. We show that polarized online echo-chambers map onto geographically situated social networks. More specifically, our results reveal that echo chambers in the Leave campaign are associated with geographic proximity and that the reverse relationship holds true for the Remain campaign. The study concludes with a discussion of primary and secondary effects arising from the interaction between existing physical ties and online interactions and argues that the collapsing of distances brought by internet technologies may foreground the role of geography within one’s social network.
  • Also important:
    • How to Write a Successful Level I DHAG Proposal
      • The idea behind a Level I project is that it can be “high risk/high reward.” Put another way, we are looking for interesting, innovative, experimental, new ideas, even if they have a high potential to fail. It’s an opportunity to figure things out so you are better prepared to tackle a big project. Because of the relatively low dollar amount (no more than $50K), we are willing to take on more risk for an idea with lots of potential. By contrast, at the Level II and especially at the Level III, there is a much lower risk tolerance; the peer reviewers expect that you’ve already completed an earlier start-up or prototyping phase and will want you to convince them your project is ready to succeed.
  • Tracing a Meme From the Internet’s Fringe to a Republican Slogan
    • This feedback loop is how #JobsNotMobs came to be. In less than two weeks, the three-word phrase expanded from corners of the right-wing internet onto some of the most prominent political stages in the country, days before the midterm elections.
  • Effectiveness of gaming for communicating and teaching climate change
    • Games are increasingly proposed as an innovative way to convey scientific insights on the climate-economic system to students, non-experts, and the wider public. Yet, it is not clear if games can meet such expectations. We present quantitative evidence on the effectiveness of a simulation game for communicating and teaching international climate politics. We use a sample of over 200 students from Germany playing the simulation game KEEP COOL. We combine pre- and postgame surveys on climate politics with data on individual in-game decisions. Our key findings are that gaming increases the sense of personal responsibility, the confidence in politics for climate change mitigation, and makes more optimistic about international cooperation in climate politics. Furthermore, players that do cooperate less in the game become more optimistic about international cooperation but less confident about politics. These results are relevant for the design of future games, showing that effective climate games do not require climate-friendly in-game behavior as a winning condition. We conclude that simulation games can facilitate experiential learning about the difficulties of international climate politics and thereby complement both conventional communication and teaching methods.
    • This reinforces the my recent thinking that games may be a fourth, distinct form of human sociocultural communication

Phil 10.29.18

7:00 – 5:00 ASRC PhD

  • This looks like a Big Deal from Google – Working together to apply AI for social good
    • Google.org is issuing an open call to organizations around the world to submit their ideas for how they could use AI to help address societal challenges. Selected organizations will receive support from Google’s AI experts, Google.org grant funding from a $25M pool, credit and consulting from Google Cloud, and more.
    • We look forward to receiving your application on or before 11:59 p.m. PT on January 22, 2019, and we encourage you to apply early given that we expect high volume within the last few hours of the application window. Thank you!
    • Application Guide
    • Application form (can’t save, compose offline using guide, above)
  • Finished my writeup on Meltdown
  • Waiting for a response from Antonio
  • Meeting with Don at 9:00 to discuss BAA partnership.
    • Don is comfortable with being PI or co-PI, whichever works best. When we call technical POCs, we speak on his behalf
    • We discussed how he could participate with the development of theoretical models based on signed graph Laplacians creating structures that can move in belief space. He thinks the idea has merit, and can put in up to 30% of his time on mathematical models and writing
    • ASRC has already partnered with UMBC. ASRC would sub to UMBC
    • Ordinarily, IP is distributed proportional to the charged hours
    • Don has access to other funding vehicles that can support the Army BAA, but this would make things more complicated. These should be discussed if we can’t make a “clean” agreement that meets our funding needs
  • Pinged Brian about his defense.
  • Some weekend thoughts
    • Opinion dynamics systems describe how communication within a network occurs, but disregards the motion of the network as a whole. In cases when the opinions converge, the network is stiff.
    • Graph laplacians could model “othering” by having negative weights. It looks like these are known as signed laplacians, and useful to denote difference. The trick is to discover the equations of motion. How do you model a “social particle”?
  • Just discovered the journal Swarm Intelligence
    • Swarm Intelligence is the principal peer reviewed publication dedicated to reporting research and new developments in this multidisciplinary field. The journal publishes original research articles and occasional reviews on theoretical, experimental, and practical aspects of swarm intelligence. It offers readers reports on advances in the understanding and utilization of systems that are based on the principles of swarm intelligence. Emphasis is given to such topics as the modeling and analysis of collective biological systems; application of biological swarm intelligence models to real-world problems; and theoretical and empirical research in ant colony optimization, particle swarm optimization, swarm robotics, and other swarm intelligence algorithms. Articles often combine experimental and theoretical work.
  • I think it’s time to start ramping up on the text generation!
      • Updated my home box to tensorflow 1.11.0. Testing to see if it still works using the Deep Learning with Keras simple_nueral_net.py example. Hasn’t broken (yet…), but is taking a long time… Worked! And it’s much faster the second time. Don’t know why that is and can’t find anything online that talks to that.
        Loss: 0.5043802047491074
        Accuracy: 0.8782
        Time =  211.42629722093085
      • Found this keras example for generating Nietsche

     

    • Trying it out. This may be a overnight run… But it is running.
  • Had a good discussion with Aaron about how mapmaking could be framed as an ML problem. More writeup tomorrow.

Phil 10.16.18

7:00 – 4:00 ASRC DARPA

  • Steve had some good questions about quantitative measures:
    • I think there are some good answers that we can provide here on determining the quality of maps. The number of users is an educated guess though. In my simulations, I can generate enough information to create maps using about 100 samples per agent. I’m working on a set of experiments that will produce “nosier” data that will provide a better estimate, but that won’t be ready until December. So we can say that “simulations indicate that approximately 100 users will have to interact through a total of 100 threaded posts to produce meaningful maps”
    • With respect to the maps themselves, we can determine quality in four ways. The mechanism for making this comparison will be bootstrap sampling (https://en.wikipedia.org/wiki/Bootstrapping_(statistics)), which is an extremely effective way of comparing two unknown distributions. In our case, the distribution will be the coordinate of each topic in the embedding space.
      1. Repeatability: Can multiple maps generated on the same data set be made to align? Embedding algorithms often start with random values. As such embeddings that are similar may appear different because they have different orientations. To determine similarity we would apply a least-squares transformation of one map with respect to the other. Once complete, we would expect a greater than 90% match between the two maps in success.
      2. Resolution: What is the smallest level of detail that can be rendered accurately? We will be converting words into topics and then placing the topics in an embedding space. As described in the document, we expect to do this with Non-Negative Matrix Factorization (NMF). If we factor the all discussions down to a single topic (i.e. “words”), then we will have a single point map that can always be rendered with 100% repeatability, but it has 0% precision. If, on the other hand, we can place every word in every discussion on the map, but the relationships are different every time, then we can have 100% precision, but 0% repeatability. As we cluster terms together, we need to compare repeated runs to see that we get similar clusters each time. We need to find the level of abstraction that will give us a high level of repeatability. A 90% match is our expectation.
      3. Responsiveness: Maps change over time. A common example is a weather map, though political maps shift borders and physical maps reflect geographic activity like shoreline erosion. This duration may reflect the accuracy of the map, with slow change happening across large scales while rapid changes are visible at higher resolutions. A change at the limit of resolution should ideally be reflected immediately in the map and not adjust the surrounding areas.
  • More frantic flailing to meet the deadline. DONE!!!

4:00 – 5:30 Antonio Workshop

Phil 10.15.18

7:00 – ASRC BD

  • Heard about some interesting things this morning on BBC Business Daily – Is the Internet Fit for Purpose?:
    • Future in Review Conference: The leading global conference on the intersection of technology and the economy. New partnerships, projects, and plans you can’t afford to miss. If your success depends on having an accurate view of the future, or you’d like to meet others who are able and motivated to forge action-based alliances, this is the most important conference you will attend. Be one of the thought leaders in the FiRe conversation, analyzing and creating the future of technology, economics, pure science, the environment, genomics, education, and more.
    • Berit Anderson. Created the science fact/fiction magazine Scout, which, interestingly enough, has a discussion space for JuryRoom-style questions
  • More DARPA proposal