7:00 – 4:30 ASRC PhD/NASA

Somehow, this needs to get into a discussion of the trustworthiness of maps

• I realized that we can hand-code these initial dungeons, learn a lot and make this a baseline part of the study. This means that we can compare human and machine data extraction for map making. My initial thoughts as to the sequence are:
  • Step 1: Finish running the initial dungeon
  • Step 2: researchers determine a set of common questions that would be appropriate for each room. Something like:
    • Who is the character?
    • Where is the character?
    • What is the character doing?
    • Why is the character doing this?
  • Each answer should also include a section of the text that the reader thinks answers that question. Once this has been worked out on paper, a simple survey website (simpler) can be built that automates this process and supports data collection at moderate scales.
  • Use answers to populate a “Trajectories” sheet in an xml file and build a map!
  • Step 3: Partially automate the extraction to give users a generated survey that lets them select the most likely answer/text for the who/where/what/why questions. Generate more maps!
  • Step 4: Full automation
• Added these thoughts to the analysis section of the google doc
• The 11th International Natural Language Generation Conference
  • The INLG conference is the main international forum for the presentation and discussion of all aspects of Natural Language Generation (NLG), including data-to-text, concept-to-text, text-to-text and vision to-text approaches. Special topics of interest for the 2018 edition included:
    • Generating Text with Affect, Style and Personality,
    • Conversational Interfaces, Chatbots and NLG, and
    • Data-driven NLG (including the E2E Generation Challenge)
• Back to grokking DNNs
  • Still building a SimpleLayer class that will take a set of neurons and create a weight array that will point to the next layer
  • array formatting issues. Tricky
  • I think I’m done enough to start debugging. Tomorrow
• Sprint review