Search results for "explicable"

showing 3 items of 3 documents

Apprentissage automatique de réseaux d'interaction à partir de données de séquences de nouvelle génération

2022

Climate change and other human-induced processes are modifying ecosystems, globally, at an ever increasing rate. Microbial communities play an important role in the functioning ecosystems, maintaining their diversity and services. These communities are shaped by the different abiotic environmental effects to which they are subjected and the biotic interactions between all community members. The ANR Next-Generation Biomonitoring (NGB) project proposed to reconstruct interaction networks from abundance measures obtained sequencing environmental DNA (eDNA) and to use these networks to monitor ecosystem change. In this thesis, conducted as part of the NGB project, I evaluate the potential of tw…

Abductive/Inductive Logic Programming (A/ILP)apprentissage automatique explicableInteraction networksbiological controlséquençage de nouvelle générationmicrobial ecologygrapevine[SDE.BE] Environmental Sciences/Biodiversity and Ecology[SDV] Life Sciences [q-bio]Plasmopara viticolamicrobiomesréseaux d'InteractionNext-Generation sequencingbiomonitoringexplainable machine learning
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Toward Artificial Intuition

2019

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]OntologyOntologieFouille de donnéesinferClustering[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]InférenceIntelligence Artificielle[INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT]Artificial IntelligenceexplainabilityexplicableData Mining[INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT]
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Expliquer le comportement de robots distants à des utilisateurs humains : une approche orientée-agent

2020

With the widespread use of Artificial Intelligence (AI) systems, understanding the behavior of intelligent agents and robots is crucial to guarantee smooth human-agent collaboration since it is not straightforward for humans to understand the agent’s state of mind. Recent studies in the goal-driven Explainable AI (XAI) domain have confirmed that explaining the agent’s behavior to humans fosters the latter’s understandability of the agent and increases its acceptability. However, providing overwhelming or unnecessary information may also confuse human users and cause misunderstandings. For these reasons, the parsimony of explanations has been outlined as one of the key features facilitating …

[SPI.OTHER]Engineering Sciences [physics]/OtherHuman-Computer InteractionExplainable Artificial IntelligenceIntelligence artificielle explicable[SPI.OTHER] Engineering Sciences [physics]/OtherMulti-Agent SystemsSystèmes multi-AgentsInteraction homme-Machine
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