Death and Suicide in Universal Artificial Intelligence
Authors: Jarryd Martin, Tom Everitt, Marcus Hutter
Reinforcement learning (RL) is a general paradigm for studying intelligent behaviour, with applications ranging from artificial intelligence to psychology and economics. AIXI is a universal solution to the RL problem; it can learn any computable environment. A technical subtlety of AIXI is that it is defined using a mixture over semimeasures that need not sum to 1, rather than over proper probabil...
DeepMPTB: a vaginal microbiome-based deep neural network as artificial intelligence strategy for efficient preterm birth prediction
Authors: Oshma Chakoory, Vincent Barra, Emmanuelle Rochette
<jats:title>Abstract</jats:title><jats:p>In recent decades, preterm birth (PTB) has become a significant research focus in the healthcare field, as it is a leading cause of neonatal mortality worldwide. Using five independent study cohorts including 1290 vaginal samples from 561 pregnant women who delivered at term (<jats:italic>n</jats:italic>β=β1029) or prematurely (<jats:italic>n</jats:italic>β...
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Published: 2024-2-14
π Source: CrossRef
π Citations: 9
Creative Problem Solving in Artificially Intelligent Agents: A Survey and Framework
Authors: Evana Gizzi, Lakshmi Nair, Sonia Chernova
Creative Problem Solving (CPS) is a sub-area within Artificial Intelligence (AI) that focuses on methods for solving off-nominal, or anomalous problems in autonomous systems. Despite many advancements in planning and learning, resolving novel problems or adapting existing knowledge to a new context, especially in cases where the environment may change in unpredictable ways post deployment, remains...