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Formal verification for safe deep reinforcement learning in trajectory generation
We consider the problem of Safe Deep Reinforcement Learning (DRL) using formal
verification in a trajectory generation task. In more detail, we propose an approach to verify …
verification in a trajectory generation task. In more detail, we propose an approach to verify …
Reciph: Relational coefficients for input partitioning heuristic
With the rapidly advancing improvements to the already successful Deep Learning artifacts,
Neural Networks (NN) are poised to permeate a growing number of everyday applications …
Neural Networks (NN) are poised to permeate a growing number of everyday applications …
Enhancing Exploration and Safety in Deep Reinforcement Learning
E Marchesini - 2022 - iris.univr.it
Abstract A Deep Reinforcement Learning (DRL) agent tries to learn a policy maximizing a
long-term objective by trials and errors in large state spaces. However, this learning …
long-term objective by trials and errors in large state spaces. However, this learning …
[PDF][PDF] Formale Verifikation ethischer Entscheidungen bei autonomen Systemen
B Fresz - ias.uni-stuttgart.de
Autonom agierende Agenten handeln zunehmend in räumlicher Nähe zu Menschen,
wodurch das sichere und ethisch korrekte Verhalten der Agenten immer wichtiger wird. Um …
wodurch das sichere und ethisch korrekte Verhalten der Agenten immer wichtiger wird. Um …