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Regular Decision Processes for Grid Worlds
Markov decision processes are typically used for sequential decision making under uncertainty.
A clustering-based reinforcement learning approach for tailored personalization of e-Health interventions
The time to learn intervention policies is limited as disengagement from the user can occur quickly.
Gatekeeping Algorithms with Human Ethical Bias: The ethics of algorithms in archives, libraries and society
In the age of algorithms, I focus on the question of how to ensure algorithms that will take over many of our familiar archival and library tasks, will behave according to human ethical norms that have evolved over many years.
From Algorithmic Black Boxes to Adaptive White Boxes: Declarative Decision-Theoretic Ethical Programs as Codes of Ethics
Ethics of algorithms is an emerging topic in various disciplines such as social science, law, and philosophy, but also artificial intelligence (AI).
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