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Multi-Task Learning as enabler for General-Purpose AI-native RAN
The realization of data-driven AI-native architecture envisioned for 6G and beyond networks can eventually lead to multiple machine learning (ML) workloads distributed at the network edges driving downstream tasks like secondary carrier prediction, positioning, channel prediction etc.
Machine Reasoning Explainability
As a field of AI, Machine Reasoning (MR) uses largely symbolic means to formalize and emulate abstract reasoning.
Properties of ABA+ for Non-Monotonic Reasoning
We investigate properties of ABA+, a formalism that extends the well studied structured argumentation formalism Assumption-Based Argumentation (ABA) with a preference handling mechanism.
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