Turhan / Trollmann | KI 2018: Advances in Artificial Intelligence | Buch | 978-3-030-00110-0 | sack.de

Buch, Englisch, 424 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 663 g

Reihe: Lecture Notes in Artificial Intelligence

Turhan / Trollmann

KI 2018: Advances in Artificial Intelligence

41st German Conference on AI, Berlin, Germany, September 24-28, 2018, Proceedings
1. Auflage 2018
ISBN: 978-3-030-00110-0
Verlag: Springer International Publishing

41st German Conference on AI, Berlin, Germany, September 24-28, 2018, Proceedings

Buch, Englisch, 424 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 663 g

Reihe: Lecture Notes in Artificial Intelligence

ISBN: 978-3-030-00110-0
Verlag: Springer International Publishing


This book constitutes the refereed proceedings of the 41st German Conference on Artificial Intelligence, KI 2018, held in Berlin, Germany, in September 2018.

The 20 full and 14 short papers presented in this volume were carefully reviewed and selected from 65 submissions. The book also contains one keynote talk in full paper length.

The papers were organized in topical sections named: reasoning; multi-agent systems; robotics; learning; planning; neural networks; search; belief revision; context aware systems; and cognitive approach. 

Turhan / Trollmann KI 2018: Advances in Artificial Intelligence jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


Keynote Talks.- Keynote: Session-based Recommendation - Challenges and Recent Advances.- Reasoning.- Model Checking for Coalition Announcement Logic.- Fusing First-order Knowledge Compilation and the Lifted Junction Tree Algorithm.- Towards Preventing Unnecessary Groundings in the Lifted Dynamic Junction Tree Algorithm.- Acquisition of Terminological Knowledge in Probabilistic Description Logic.- Multi-Agent Systems.- Group Envy Freeness and Group Pareto Efficiency in Fair Division with Indivisible Items.- Approximate Probabilistic Parallel Multiset Rewriting using MCMC.- Efficient Auction Based Coordination for Distributed Multi-Agent Planning in Temporal Domains Using Resource Abstraction.- Maximizing Expected Impact in an Agent Reputation Network.- Developing a Distributed Drone Delivery System with a Hybrid Behavior Planning System.- Robotics.- A Sequence-Based Neuronal Model for Mobile Robot Localization.- Acquiring knowledge of object arrangements from human examples for household robots.- Learning.- Solver Tuning and Model Configuration.- Condorcet's Jury Theorem for Consensus Clustering.- Sparse Transfer Classification for Text Documents.- Towards Hypervector Representations for Learning and Planning with Schemas.- LEARNDIAG: A Direct Diagnosis Algorithm Based On Learned Heuristics.- Planning.- Assembly Planning in Cluttered Environments through Heterogeneous Reasoning.- Extracting Planning Operators from Instructional Texts for Behaviour Interpretation.- Risk-Sensitivity in Simulation Based Online Planning.- Neural Networks.- Evolutionary Structure Minimization of Deep Neural Networks for Motion Sensor Data.- Knowledge Sharing For Population Based Neural Network Training.- Limited Evaluation Evolutionary Optimization of Large Neural Networks.- Understanding NLP Neural Networks by the Texts They Generate.- Visual Search Target Inference using Bag of Deep Visual Words.- Analysis and Optimization of Deep Counterfactual Value Networks.- Search. -A Variant ofMonte-Carlo Tree Search for Referring Expression Generation.- Preference-Based Monte Carlo Tree Search.- Belief Revision.- Probabilistic Belief Revision via Similarity of Worlds Modulo Evidence.- Intentional Forgetting in Artificial Intelligence Systems: Perspectives and Challenges.- Kinds and Aspects of Forgetting in Common-Sense Knowledge and Belief Management.- Context Aware Systems.- Bounded-Memory Stream Processing.- An Implementation and Evaluation of User-centered Requirements for Smart In-House Mobility Services.- Cognitive Approach.- Predict the Individual Reasoner: A New Approach.- The Predictive Power of Heuristic Portfolios in Human Syllogistic Reasoning.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.