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of 4
pro vyhledávání: '"Córdoba, Filip Cano"'
Autor:
Córdoba, Filip Cano, Palmisano, Alexander, Fränzle, Martin, Bloem, Roderick, Könighofer, Bettina
Agents operating in physical environments need to be able to handle delays in the input and output signals since neither data transmission nor sensing or actuating the environment are instantaneous. Shields are correct-by-construction runtime enforce
Externí odkaz:
http://arxiv.org/abs/2307.02164
Autor:
Córdoba, Filip Cano, Judson, Samuel, Antonopoulos, Timos, Bjørner, Katrine, Shoemaker, Nicholas, Shapiro, Scott J., Piskac, Ruzica, Könighofer, Bettina
Principled accountability for autonomous decision-making in uncertain environments requires distinguishing intentional outcomes from negligent designs from actual accidents. We propose analyzing the behavior of autonomous agents through a quantitativ
Externí odkaz:
http://arxiv.org/abs/2307.01532
Evaluation of deep reinforcement learning (RL) is inherently challenging. Especially the opaqueness of learned policies and the stochastic nature of both agents and environments make testing the behavior of deep RL agents difficult. We present a sear
Externí odkaz:
http://arxiv.org/abs/2205.04887
Autor:
Judson, Samuel, Elacqua, Matthew, Córdoba, Filip Cano, Antonopoulos, Timos, Könighofer, Bettina, Shapiro, Scott J., Piskac, Ruzica
Principled accountability in the aftermath of harms is essential to the trustworthy design and governance of algorithmic decision making. Legal philosophy offers a paramount method for assessing culpability: putting the agent 'on the stand' to subjec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec4026ba488d485d34d6acde052b7f04