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Week 1

In week 1 we met up on the following days:

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  • Kiran: look into the libraries useful for extracting features from the environment that can be used for Personalisation and Reinforcement Learning. Features to be extracted are:

    • Age

    • Clothing

      • There were problems in installing the libraries tensorflow and keras because of the MacOS and python version in the system resulting in conflicts.

        • Error - zsh: illegal hardware instruction python

      • Ran into a problem when installing mediapipe, but was resolved:

        • Error - No matching distribution found for mediapipe mac

          • Solution : Step 1 - Install Rosetta 2 ( /usr/sbin/softwareupdate --install-rosetta)

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What did we work on?

Monday 10:00 - 16:30

  • Make presentation (Siddhant)

  • Look into training dataset age detection model (Mincke)

  • Research into MAB (Siddhant & Kiran)

  • Trouble-shooting merging the files (Mincke)

  • Update logbook with feedback & start case study (Mincke)

Tuesday 10:00 - 17:00

  • Perform case study with 12 participants (Siddhant & Mincke)

  • Change bows in Choregraphe (S&M)

  • Meeting with Buelent about MAB and SA (Kiran)

Thursday 9:15 - 17:30

  • Dialogflow issues

  • Implementing the learning part

  • Merging all parts together

Friday 9:15 - 15:00

  • Final touched

  • Final presentation + demo

Monday 31.1

Unfortuately we did not have access to the lab today, so we worked on the VU together on the presentation and stuff we could do without having the robots available.

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  • Gt is the encoded feedback.

    • The feedback means either to:

      • increase duration

      • decrease duration

      • stop

    • If the feedback means to increase, Gt would be a positive value.

    • But since we want to increase the duration, we do not want any negative value while updating that would decrease the thetamu

    • Therefore we check if :

      Image RemovedImage Added

(where At is the prior duration action, mutheta(St) is the mean of the Age range), is positive or negative. If the difference is negative and the feedback means to increase, Gt would be a negative value(say -0.1) and if the feedback is meant to increase and if the difference is positive, Gt would be a positive value(say 0.1).

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