On imperfect recall in multi-agent influence diagrams
Multi-agent influence diagrams (MAIDs) are a popular game-theoretic model based on
Bayesian networks. In some settings, MAIDs offer significant advantages over extensive …
Bayesian networks. In some settings, MAIDs offer significant advantages over extensive …
Probabilistic inference in credal networks: new complexity results
DD Mauá, CP de Campos, A Benavoli… - Journal of Artificial …, 2014 - jair.org
Credal networks are graph-based statistical models whose parameters take values in a set,
instead of being sharply specified as in traditional statistical models (eg, Bayesian …
instead of being sharply specified as in traditional statistical models (eg, Bayesian …
Optimal sequence of tests for the mediastinal staging of non-small cell lung cancer
Background Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer
and the most difficult to predict. When there are no distant metastases, the optimal therapy …
and the most difficult to predict. When there are no distant metastases, the optimal therapy …
[图书][B] Modeling and analysis of dependable systems: a probabilistic graphical model perspective
L Portinale, DC Raiteri - 2015 - books.google.com
The monographic volume addresses, in a systematic and comprehensive way, the state-of-
the-art dependability (reliability, availability, risk and safety, security) of systems, using the …
the-art dependability (reliability, availability, risk and safety, security) of systems, using the …
[HTML][HTML] Equivalences between maximum a posteriori inference in bayesian networks and maximum expected utility computation in influence diagrams
DD Mauá - International Journal of Approximate Reasoning, 2016 - Elsevier
Two important tasks in probabilistic reasoning are the computation of the maximum posterior
probability of a given subset of the variables in a Bayesian network (MAP), and the …
probability of a given subset of the variables in a Bayesian network (MAP), and the …
Decision networks for security risk assessment of critical infrastructures
D Codetta-Raiteri, L Portinale - ACM Transactions on Internet …, 2018 - dl.acm.org
We exploit Decision Networks (DN) for the analysis of attack/defense scenarios in critical
infrastructures. DN extend Bayesian Networks (BN) with decision and value nodes. DN …
infrastructures. DN extend Bayesian Networks (BN) with decision and value nodes. DN …
Modelling other agents through evolutionary behaviours
Y Zeng, Q Ran, B Ma, Y Pan - Memetic Computing, 2022 - Springer
Modelling other agents is a challenging topic in artificial intelligence research particularly
when a subject agent needs to optimise its own decisions by predicting their behaviours …
when a subject agent needs to optimise its own decisions by predicting their behaviours …
On the complexity of strong and epistemic credal networks
DD Mauá, CP De Campos, A Benavoli… - arXiv preprint arXiv …, 2013 - arxiv.org
Credal networks are graph-based statistical models whose parameters take values in a set,
instead of being sharply specified as in traditional statistical models (eg, Bayesian …
instead of being sharply specified as in traditional statistical models (eg, Bayesian …
A weighted mini-bucket bound for solving influence diagram
Influence diagrams provide a modeling and inference framework for sequential decision
problems, representing the probabilistic knowledge by a Bayesian network and the …
problems, representing the probabilistic knowledge by a Bayesian network and the …
Quads: question answering for decision support
As the scale of available on-line data grows ever larger, individuals and businesses must
cope with increasing complexity in decision-making processes which utilize large volumes …
cope with increasing complexity in decision-making processes which utilize large volumes …