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Personal profile

Research interests

PhD student in Explainable AI for Black Box Autonomous Agents

My research explores how we might begin to understand and explain the policies of black box autonomous agents, whose internal mechanisms and representations may be very different from our own, with a particular view to revealing the biases and flaws in their decision-making. Critical to this question are the putative trade-off between comprehensibility and performance of machine learning models, and the thorny relationship between correlation and causation in observed data whose generative origins are unknown.

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Research Output

  • 2 Conference Paper
  • 1 Conference Contribution (Conference Proceeding)

Modelling Agent Policies with Interpretable Imitation Learning

Bewley, T., Lawry, J. & Richards, A. G., 4 Sep 2020, (Accepted/In press).

Research output: Contribution to conferenceConference Paper

  • On the Combination of Gamification and Crowd Computation in Industrial Automation and Robotics Applications

    Bewley, T. & Liarokapis, M., 12 Aug 2019, 2019 International Conference on Robotics and Automation (ICRA).

    Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

  • On Tour: Harnessing Social Tourism Data for City and Point of Interest Recommendation

    Bewley, T., 21 Nov 2019, p. 51-56.

    Research output: Contribution to conferenceConference Paper