Titlebook: KI 2023: Advances in Artificial Intelligence; 46th German Conferen Dietmar Seipel,Alexander Steen Conference proceedings 2023 The Editor(s)

競選運(yùn)動(dòng)

,Object Anchoring for?Autonomous Robots Using the?Spatio-Temporal-Semantic Environment Representatiol high-resolution sensor data. ., the Spatio-Temporal-Semantic Environment Representation, can be used to structure and manage such data more efficiently. . deals with the spatial, temporal and semantic modalities of data simultaneously and provides an efficient query interface for all three modalit

Cantankerous

一起平行

,Computing Most Likely Scenarios of?Qualitative Constraint Networks,ncies may arise in various application contexts, such as merging data from different sources. Here, identifying a consistent constraint network that deviates as little as possible from the over-constrained network is of great interest. This problem of . an inconsistent network is a challenging optim

extrovert

內(nèi)疚

,Generating Synthetic Dialogues from?Prompts to?Improve Task-Oriented Dialogue Systems,ne special case of chatbots is that of Task-Oriented Dialogue (TOD) systems that aim to help the user achieve specific tasks using external services. High quality training data for these systems is costly to come by. We thus evaluate if the new prompt-following models can generate annotated syntheti

即席演說

,Flexible Automation of?Quantified Multi-Modal Logics with?Interactions,cular in knowledge representation and reasoning, modal logic formalisms often employ multiple modalities with different properties and intricate interaction schemes. In this paper, a format for representing such non-trivial modal logic set-ups, and reasoning problems within these logics, is presente

串通

Meander

978-3-031-42607-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

MAZE

KI 2023: Advances in Artificial Intelligence978-3-031-42608-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

割讓