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Uncertainty-aware situational understanding
(SPIE, 2019)
Situational understanding is impossible without causal reasoning and reasoning under and about uncertainty, i.e. prob-abilistic reasoning and reasoning about the confidence in the uncertainty assessment. We therefore ...
Learning and reasoning in complex coalition information environments: a critical analysis
(IEEE, 2018-09-05)
In this paper we provide a critical analysis with metrics that will inform guidelines for designing distributed systems for Collective Situational Understanding (CSU). CSU requires both collective insight - i.e., accurate ...
Handling epistemic and aleatory uncertainties in probabilistic circuits
(Springer, 2022-04)
When collaborating with an AI system, we need to assess when to trust its recommendations. If we mistakenly trust it in regions where it is likely to err, catastrophic failures may occur, hence the need for Bayesian ...
Probabilistic logic programming with beta-distributed random variables
(Association for the Advancement of Artificial Intelligence, 2019-07-17)
We enable aProbLog-a probabilistic logical programming approach-to reason in presence of uncertain probabilities represented as Beta-distributed random variables. We achieve the same performance of state-of-the-art algorithms ...
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