Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Federico Cerutti"'
Publikováno v:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II.
Coalition situational understanding (CSU) is fundamental to support decision-making and autonomy in multi-domain operations involving multiple allied partners. Our work aims to advance the algorithms and techniques to develop CSU, addressing key scie
Autor:
Lance M. Kaplan, Supriyo Chakraborty, Mani Srivastava, Gavin Pearson, Richard Tomsett, Alun Preece, Federico Cerutti, Dave Braines
Publikováno v:
Patterns, Vol 1, Iss 4, Pp 100049-(2020)
Patterns
Patterns
Artificial intelligence (AI) systems hold great promise as decision-support tools, but we must be able to identify and understand their inevitable mistakes if they are to fulfill this potential. This is particularly true in domains where the decision
Autor:
Ramya Raghavendra, Mani Srivastava, Moustafa Alzantot, Supriyo Chakraborty, Jonathan Z. Bakdash, Murat Sensoy, Tianwei Xing, Alun Preece, Lance M. Kaplan, Angelika Kimmig, Daniel Harborne, Federico Cerutti, Dave Braines
Publikováno v:
FUSION
Fusion 2018: 21st International Conference on Information Fusion
Fusion 2018: 21st International Conference on Information Fusion
In this paper we provide a critical analysis with met- rics that will inform guidelines for designing distributed systems for Collective Situational Understanding (CSU). CSU requires both collective insight—i.e., accurate and deep understanding of
Publikováno v:
Next-Generation Analyst VI.
Many important decisions historically made by humans are now being made by algorithms - often learnt from data - whose accountability measures and legal standards are far from satisfactory. While model transparency is important, it is neither necessa
Autor:
Dave Braines, Alun Preece, Anna Thomas, Federico Cerutti, Jonathan Z. Bakdash, Murat Sensoy, Magdalena Ivanovska, Lance M. Kaplan
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319781013
GKR
GKR
Due to copyright restrictions, the access to the full text of this article is only available via subscription. In this paper we present a methodology to exploit human-machine coalitions for situational understanding. Situational understanding refers
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f9530751d7f904b6ce481026de961d3
https://orca.cardiff.ac.uk/id/eprint/107285/1/_Extended_Version__Subjective_Bayesian_Networks_and_Human_in_the_Loop_Situational_Understanding.pdf
https://orca.cardiff.ac.uk/id/eprint/107285/1/_Extended_Version__Subjective_Bayesian_Networks_and_Human_in_the_Loop_Situational_Understanding.pdf
Autor:
Gavin Pearson, Federico Cerutti
Publikováno v:
Fusion 2018: 21st International Conference on Information Fusion
FUSION
FUSION
In this paper we propose a computational method- ology for assessing the impact of trust associated to sources of information in scientific enquiry activities building upon recent proposals of an ontology for situational understanding and results in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e339f5b10d40e09f5d973ecb065d61f2
https://orca.cardiff.ac.uk/id/eprint/111241/1/Supporting_Scientific_Enquiry_with_Uncertain_Sources.pdf
https://orca.cardiff.ac.uk/id/eprint/111241/1/Supporting_Scientific_Enquiry_with_Uncertain_Sources.pdf