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ORCIDJournal of Artificial Intelligence Research, Volume 69
Volume 69, 2020
- Pavlos Vougiouklis, Eddy Maddalena
, Jonathon S. Hare, Elena Simperl:
Point at the Triple: Generation of Text Summaries from Knowledge Base Triples. 1-31
- Emmanuel Hebrard, George Katsirelos:
Constraint and Satisfiability Reasoning for Graph Coloring. 33-65 - Luis E. Ortiz:
On Sparse Discretization for Graphical Games. 67-84 - Theofanis I. Aravanis, Pavlos Peppas, Mary-Anne Williams:
Incompatibilities Between Iterated and Relevance-Sensitive Belief Revision. 85-108 - Paul W. Goldberg, Alexandros Hollender, Warut Suksompong:
Contiguous Cake Cutting: Hardness Results and Approximation Algorithms. 109-141 - Mücahid Kutlu, Tyler McDonnell, Tamer Elsayed, Matthew Lease:
Annotator Rationales for Labeling Tasks in Crowdsourcing. 143-189 - Siddharth Gupta, Guy Sa'ar, Meirav Zehavi:
The Parameterized Complexity of Motion Planning for Snake-Like Robots. 191-229 - Peng Lin, Martin Neil, Norman E. Fenton:
Improved High Dimensional Discrete Bayesian Network Inference using Triplet Region Construction. 231-295 - Jacopo Banfi, Vikram Shree, Mark E. Campbell:
Planning High-Level Paths in Hostile, Dynamic, and Uncertain Environments. 297-342 - Felix Stahlberg:
Neural Machine Translation: A Review. 343-418 - Mohammad Ali Javidian, Marco Valtorta, Pooyan Jamshidi:
AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms. 419-470 - Shih-Yun Lo, Shiqi Zhang, Peter Stone:
The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation. 471-500 - Milos Chromý, Ondrej Cepek:
Properties of Switch-List Representations of Boolean Functions. 501-529 - Vitor Bosshard, Benedikt Bünz, Benjamin Lubin, Sven Seuken:
Computing Bayes-Nash Equilibria in Combinatorial Auctions with Verification. 531-570 - Iulian Vlad Serban, Chinnadhurai Sankar, Michael Pieper, Joelle Pineau, Yoshua Bengio:
The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach. 571-612 - Miroslaw Truszczynski, Zbigniew Lonc:
Maximin Share Allocations on Cycles. 613-655 - Nerio Borges, Ramón Pino Pérez:
Belief change and 3-valued logics: Characterization of 19, 683 belief change operators. 657-685 - Ulle Endriss, Ronald de Haan, Jérôme Lang, Marija Slavkovik:
The Complexity Landscape of Outcome Determination in Judgment Aggregation. 687-731 - Ata Kabán, Robert J. Durrant:
Structure from Randomness in Halfspace Learning with the Zero-One Loss. 733-764 - Senka Krivic, Michael Cashmore, Daniele Magazzeni, Sándor Szedmák, Justus H. Piater:
Using Machine Learning for Decreasing State Uncertainty in Planning. 765-806 - Joseph Bullock, Alexandra Sasha Luccioni, Katherine Hoffmann Pham, Cynthia Sin Nga Lam, Miguel A. Luengo-Oroz:
Mapping the landscape of Artificial Intelligence applications against COVID-19. 807-845 - Marco Amoruso, Daniele Anello, Vincenzo Auletta, Raffaele Cerulli, Diodato Ferraioli, Andrea Raiconi:
Contrasting the Spread of Misinformation in Online Social Networks. 847-879 - The Anh Han, Luís Moniz Pereira, Francisco C. Santos, Tom Lenaerts:
To Regulate or Not: A Social Dynamics Analysis of an Idealised AI Race. 881-921 - Blai Bonet, Hector Geffner:
Qualitative Numeric Planning: Reductions and Complexity. 923-961 - Chiara Del Vescovo, Matthew Horridge, Bijan Parsia, Uli Sattler, Thomas Schneider, Haoruo Zhao:
Modular Structures and Atomic Decomposition in Ontologies. 963-1021 - Marco Garapa, Eduardo Fermé, Maurício D. Luís Reis:
Credibility-limited Base Revision: New Classes and Their Characterizations. 1023-1075 - Artem Kaznatcheev, David A. Cohen, Peter Jeavons:
Representing Fitness Landscapes by Valued Constraints to Understand the Complexity of Local Search. 1077-1102 - Chiaki Sakama, Tran Cao Son:
Epistemic Argumentation Framework: Theory and Computation. 1103-1126 - Yuan Luo, Nicholas R. Jennings:
A Differential Privacy Mechanism that Accounts for Network Effects for Crowdsourcing Systems. 1127-1164 - Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer:
Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning. 1165-1201 - Stefan Lüdtke, Thomas Kirste:
Lifted Bayesian Filtering in Multiset Rewriting Systems. 1203-1254 - Ricardo Cardoso Pereira, Miriam Seoane Santos, Pedro Pereira Rodrigues, Pedro Henriques Abreu:
Reviewing Autoencoders for Missing Data Imputation: Technical Trends, Applications and Outcomes. 1255-1285 - Cam Linke, Nadia M. Ady, Martha White, Thomas Degris, Adam White:
Adapting Behavior via Intrinsic Reward: A Survey and Empirical Study. 1287-1332 - Benjamin Fish, Lev Reyzin:
On the Complexity of Learning a Class Ratio from Unlabeled Data. 1333-1349 - Amit K. Chopra, Samuel H. Christie V., Munindar P. Singh:
An Evaluation of Communication Protocol Languages for Engineering Multiagent Systems. 1351-1393 - Petr Kucera, Petr Savický:
Bounds on the Size of PC and URC Formulas. 1395-1420 - Aristotelis Lazaridis, Anestis Fachantidis, Ioannis P. Vlahavas:
Deep Reinforcement Learning: A State-of-the-Art Walkthrough. 1421-1471 - Gianfranco Lamperti, Marina Zanella, Xiangfu Zhao:
Diagnosis of Deep Discrete-Event Systems. 1473-1532
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