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Filtering by: Creator Arthur, Samuel Codjoe Committee Member Tadepalli, Prasad Decade 2020-2029

Re-understanding Finite-State Representations of Recurrent Policy Networks

Creator:

Danesh, Mohamad H.

Abstract:

We propose an approach for understanding control policies represented as recurrent neural networks. Recent work has approached this problem by transforming such recurrent policy networks into finite-state machines (FSM) and then analyzing the equivalent minimized FSM. While this led to interesting insights, the minimization process can obscure a deeper understanding...

Resource Type:

Masters Thesis
Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

Creator:

Dodge, Jonathan E.

Abstract:

Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...

Resource Type:

Dissertation