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View article: AI Alignment with Changing and Influenceable Reward Functions
AI Alignment with Changing and Influenceable Reward Functions Open
Existing AI alignment approaches assume that preferences are static, which is unrealistic: our preferences change, and may even be influenced by our interactions with AI systems themselves. To clarify the consequences of incorrectly assumi…
View article: When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback
When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback Open
Past analyses of reinforcement learning from human feedback (RLHF) assume that the human evaluators fully observe the environment. What happens when human feedback is based only on partial observations? We formally define two failure cases…
View article: Evaluation of the Use of Combined Artificial Intelligence and Pathologist Assessment to Review and Grade Prostate Biopsies
Evaluation of the Use of Combined Artificial Intelligence and Pathologist Assessment to Review and Grade Prostate Biopsies Open
In this study, the use of an AI-based assistive tool for the review of prostate biopsies was associated with improvements in the quality, efficiency, and consistency of cancer detection and grading.
View article: Development and Validation of a Deep Learning Algorithm for Gleason Grading of Prostate Cancer From Biopsy Specimens
Development and Validation of a Deep Learning Algorithm for Gleason Grading of Prostate Cancer From Biopsy Specimens Open
In this study, the DLS showed higher proficiency than general pathologists at Gleason grading prostate needle core biopsy specimens and generalized to an independent institution. Future research is necessary to evaluate the potential utili…
View article: Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer
Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer Open
For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage. However, Gleason scoring is based on subjective microscopic examination of tumor m…
View article: #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning Open
Count-based exploration algorithms are known to perform near-optimally when used in conjunction with tabular reinforcement learning (RL) methods for solving small discrete Markov decision processes (MDPs). It is generally thought that coun…