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ORCIDHuman-Like Machine Intelligence 2022
- Stephen H. Muggleton, Nicholas Chater:
Human-Like Machine Intelligence. Oxford University Press 2022, ISBN 9780191895333
Part 1: Human-Like Machine Intelligence
- Stuart Russell:
Human-Compatible Artificial Intelligence. 3-23 - Peter Millican:
Alan Turing and Human-Like Intelligence. 24-51 - Nick Chater, Jennifer Misyak:
Spontaneous Communicative Conventions through Virtual Bargaining. 52-67 - Alan Bundy, Eugene Philalithis, Xue Li
:
Modelling Virtual Bargaining using Logical Representation Change. 68-90
Part 2: Human-Like Social Cooperation
- Oana Cocarascu, Kristijonas Cyras, Antonio Rago, Francesca Toni:
Mining Property-driven Graphical Explanations for Data-centric AI from Argumentation Frameworks. 93-113 - Marko Tesic, Ulrike Hahn:
Explanation in AI systems. 114-136 - Patrick G. T. Healey:
Human-like Communication. 137-151 - Rose E. Wang, Sarah A. Wu, James A. Evans, David C. Parkes, Joshua B. Tenenbaum, Max Kleiman-Weiner:
Too Many cooks: Bayesian inference for coordinating Multi-agent Collaboration. 152-170 - José Hernández-Orallo, Cèsar Ferri:
Teaching and Explanation: Aligning Priors between Machines and Humans. 171-196
Part 3: Human-Like Perception and Language
- Stephen H. Muggleton, Wang-Zhou Dai:
Human-like Computer Vision. 199-217 - Richard Evans:
Apperception. 218-238 - Alaa Alahmadi, Alan Davies, Markel Vigo, Katherine Dempsey, Caroline Jay:
Human-Machine Perception of Complex Signal Data. 239-259 - Martin J. Pickering, Simon Garrod:
The Shared-Workspace Framework for Dialogue and Other Cooperative Joint Activities. 260-273 - Beata J. Grzyb, Gabriella Vigliocco:
Beyond Robotic Speech: Mutual Benefits to Cognitive Psychology and Artificial Intelligence from the Study of Multimodal Communication. 274-294
Part 4: Human-Like Representation and Learning
- Alireza Tamaddoni-Nezhad, David A. Bohan, Ghazal Afroozi Milani, Alan Raybould, Stephen H. Muggleton:
Human-Machine Scientific Discovery. 297-315 - Denis Mareschal, Sam Blakeman:
Fast and Slow Learning in Human-Like Intelligence. 316-337 - Ute Schmid:
Interactive Learning with Mutual Explanations in Relational Domains. 338-354 - Mateja Jamnik, Peter C.-H. Cheng:
Endowing Machines with the Expert Human Ability to Select Representations: Why and How. 355-378 - Clément Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, Luc De Raedt:
Human-Machine Collaboration for Democratizing Data Science. 379-402
Part 5: Evaluating Human-like Reasoning
- Brandon Bennett, Anthony G. Cohn:
Automated Common-sense Spatial Reasoning: Still a Huge Challenge. 405-429 - Adam Sanborn, Jian-Qiao Zhu, Jake Spicer, Joakim Sundh, Pablo León-Villagrá, Nick Chater:
Sampling as the Human Approximation to Probabilistic Inference. 430-448 - Katya Tentori:
What Can the Conjunction Fallacy Tell Us about Human Reasoning? 449-464 - Claude Sammut, Reza Farid, Handy Wicaksono, Timothy Wiley:
Logic-based Robotics. 465-486 - Ivan Bratko, Dayana Hristova, Matej Guid:
Predicting Problem Difficulty in Chess. 487-504
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