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A systematic literature review on ai safety: Identifying trends, challenges and future directions
Artificial intelligence (AI) is revolutionizing many aspects of our lives, except it raises
fundamental safety and ethical issues. In this survey paper, we review the current state of …
fundamental safety and ethical issues. In this survey paper, we review the current state of …
Shielded Reinforcement Learning: A review of reactive methods for safe learning
H Odriozola-Olalde, M Zamalloa… - 2023 IEEE/SICE …, 2023 - ieeexplore.ieee.org
Reinforcement Learning (RL) algorithms are showing promising results in simulated
environments, but their replication in real physical applications, even more so in safety …
environments, but their replication in real physical applications, even more so in safety …
Safe reinforcement learning via probabilistic logic shields
WC Yang, G Marra, G Rens, L De Raedt - ar** for human-robot collaboration with transparent matrix overlays
One important aspect of effective human--robot collaborations is the ability for robots to
adapt quickly to the needs of humans. While techniques like deep reinforcement learning …
adapt quickly to the needs of humans. While techniques like deep reinforcement learning …
A learner-verifier framework for neural network controllers and certificates of stochastic systems
Reinforcement learning has received much attention for learning controllers of deterministic
systems. We consider a learner-verifier framework for stochastic control systems and survey …
systems. We consider a learner-verifier framework for stochastic control systems and survey …
Symbolic task inference in deep reinforcement learning
H Hasanbeig, NY Jeppu, A Abate, T Melham… - Journal of Artificial …, 2024 - jair.org
This paper proposes DeepSynth, a method for effective training of deep reinforcement
learning agents when the reward is sparse or non-Markovian, but at the same time progress …
learning agents when the reward is sparse or non-Markovian, but at the same time progress …
Correct-by-construction runtime enforcement in AI–A survey
Runtime enforcement refers to the theories, techniques, and tools for enforcing correct
behavior with respect to a formal specification of systems at runtime. In this paper, we are …
behavior with respect to a formal specification of systems at runtime. In this paper, we are …