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Human-Like Machine Intelligence

Stephen Muggleton and Nicholas Chater

Abstract

In recent years there has been increasing excitement concerning the potential of Artificial Intelligence to transform human society. This book addresses the leading edge of research in this area. The research described aims to address present incompatibilities of Human and Machine reasoning and learning approaches. According to the influential US funding agency DARPA (originator of the Internet and Self-Driving Cars) this new area represents the Third Wave of Artificial Intelligence (3AI, 2020s–2030s), and is being actively investigated in the US, Europe and China. The EPSRC’s UK network on Hu ... More

Keywords: Artificial Intelligence, Cognitive Science, Human Interaction, Perception, Reasoning

Bibliographic Information

Print publication date: 2021 Print ISBN-13: 9780198862536
Published to Oxford Scholarship Online: August 2021 DOI:10.1093/oso/9780198862536.001.0001

Authors

Affiliations are at time of print publication.

Stephen Muggleton, editor
Professor of Machine Learning, Imperial College London

Nicholas Chater, editor
Professor of Behavioural Science, Warwick Business School

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Contents

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Part 1 Human-Like Machine Intelligence

1 Human-Compatible Artificial Intelligence

Stuart Russell, University of California, Berkeley, USA

2 Alan Turing and Human-Like Intelligence

Peter Millican, Hertford College, Oxford, UK

3 Spontaneous Communicative Conventions through Virtual Bargaining

Nick Chater and Jennifer Misyak, Warwick Business School, UK

4 Modelling Virtual Bargaining using Logical Representation Change

Alan Bundy, Eugene Philalithis, and Xue Li, University of Edinburgh, UK

Part 2 Human-Like Social Cooperation

5 Mining Property-driven Graphical Explanations for Data-centric AI from Argumentation Frameworks

Oana Cocarascu, Kristijonas Cyras, Antonio Rago, and Francesca Toni, Imperial College London, UK

6 Explanation in AI systems

Marko Tesic and Ulrike Hahn, Department of Psychological Sciences, Birkbeck, University of London, UK

7 Human-like Communication

Patrick G. T. Healey, Queen Mary, University of London, UK

8 Too Many cooks: Bayesian inference for coordinating Multi-agent Collaboration

Rose E. Wang1, Sarah A. Wu1, James A. Evans2, David C. Parkes3, Joshua B. Tenenbaum1, and Max Kleiman-Weiner1, 3 1 Massachusetts Institute of Technology, 2 University of Chicago, and 3 Harvard University, USA

9 Teaching and Explanation: Aligning Priors between Machines and Humans

José Hernández-Orallo and Cèsar Ferri, Universitat Politècnica de València, Spain

Part 3 Human-Like Perception and Language

10 Human-like Computer Vision

Stephen Muggleton and Wang-Zhou Dai, Department of Computing, Imperial College London

11 Apperception

Richard Evans, Imperial College London and DeepMind, UK

12 Human–Machine Perception of Complex Signal Data

Alaa Alahmadi, Alan Davies, Markel Vigo, Katherine Dempsey, and Caroline Jay, University of Manchester, UK

13 The Shared-Workspace Framework for Dialogue and Other Cooperative Joint Activities

Martin J. Pickering and Simon Garrod, University of Edinburgh and University of Glasgow, UK

14 Beyond Robotic Speech: Mutual Benefits to Cognitive Psychology and Artificial Intelligence from the Study of Multimodal Communication

Beata Grzyb and Gabriella Vigliocco, University College London, Division of Psychology and Language Sciences, UK

Part 4 Human-Like Representation and Learning

15 Human–Machine Scientific Discovery

Alireza Tamaddoni-Nezhad1, 2, David Bohan3, Ghazal Afroozi Milani2, Alan Raybould4, and Stephen Muggleton2 1 University of Surrey, 2 Imperial College London, UK, 3 INRA, France, and 4 University of Edinburgh, UK

16 Fast and Slow Learning in Human-Like Intelligence

Denis Mareschal and Sam Blakeman, Birkbeck College, University of London, UK

17 Interactive Learning with Mutual Explanations in Relational Domains

Ute Schmid, Cognitive Systems Group, University of Bamberg, Germany

18 Endowing Machines with the Expert Human Ability to Select Representations: Why and How

Mateja Jamnik1 and Peter Cheng2 1 University of Cambridge and 2 University of Sussex, UK

19 Human–Machine Collaboration for Democratizing Data Science

CléMent Gautrais, Yann Dauxais, Stefano Teso, Samuel Kolb, Gust Verbruggen, and Luc De Raedt, KU Leuven, Department of Computer Science, Leuven, Belgium

Part 5 Evaluating Human-like Reasoning

20 Automated Common-sense Spatial Reasoning: Still a Huge Challenge

Brandon Bennett and Anthony G. Cohn, University of Leeds

21 Sampling as the Human Approximation to Probabilistic Inference

Adam Sanborn1, Jian-Qiao Zhu1, Jake Spicer1, Joakim Sundh1, Pablo León-Villagrá1, and Nick Chater2 1 University of Warwick and 2 Warwick Business School

22 What Can the Conjunction Fallacy Tell Us about Human Reasoning?

Katya Tentori, CIMeC, University of Trento

23 Logic-based Robotics

Claude Sammut1, Reza Farid2, Handy Wicaksono3, and Timothy Wiley4 1 University of New South Wales, 2 WiseTech Global, 3 Petra Christian University, and 4 RMIT University, Australia

24 Predicting Problem Difficulty in Chess

Ivan Bratko1, Dayana Hristova2, and Matej Guid1 1 University of Ljubljana, 2 University of Vienna

End Matter