Human-Like Machine Intelligence

Stephen Muggleton is Professor of Machine Learning in the Department of Computing at Imperial College London. He is the Director of UK EPSRC NetworkPlus on Human-Like Computing He was the founder of the field of Inductive Logic Programming to which he has made contributions in theory, implementations and applications and has over 200 publications. He has been Executive Editor of the Machine Intelligence workshop series since 1992 and Editor-in-Chief of the series since 2000. In particular he acted as Programme Chair of the Machine Intelligence 20 and 21 workshop on Human-Like Computing (Cumberland Lodge, 23-25 October 2016; 30 th June-3rd July 2019).Nick Chater FBA, Professor of Behavioural Science, Warwick Business SchoolNick works on the cognitive and social foundations of rationality. He has written over 250 publications and co-written or edited more than a dozen books, has won four national awards for psychological research, and has served as Associate Editor for the journals Cognitive Science, Psychological Review, and Psychological Science. He was elected Fellow of the Cognitive Science Society in 2010, Fellow of the British Academy in 2012, and Fellow of the Association for Psychological Science in 2014. Nick co-founded Decision Technology, a consultancy applying psychology to business; and he is a member of the UK's Committee on Climate Change. His book The Mind is Flat (Penguin/Yale University Press), won the Association of American Publishers PROSE Award for Best Book in Clinical Psychology, 2018.

• PART 1 Human-Like Machine Intelligence1: Human-Compatible Artificial Intelligence2: Alan Turing and Human-Like Intelligence3: Spontaneous communicative conventions through virtual bargaining4: Modelling virtual bargaining using logical representation change"PART 2 Human-Like Social Cooperation5: Mining Property-driven Graphical Explanations for Datacentric AI from Argumentation Frameworks6: Explanation in AI systems7: Human-Like Communication8: Too many cooks: Coordinating multi-agent collaboration through inverse planning9: Teaching and explanation: aligning priors between machines and humansPART 3 Human-Like Perception and Language10: Human-Like Computer Vision11: Apperception12: Human-Machine Perception of Complex Signal Data13: The sharedworkspace framework for dialogue and other cooperative joint activities14: Beyond robotic speech: mutual benefits to cognitive psychology and artificial intelligence from the joint study of multimodal communicationPART 4 Human-Like Representation and Learning15: Human-Machine Scientific Discovery16: Fast and slow learning in human-like intelligence17: Interactive Learning with Mutual Explanations in Relational Domains18: Endowing machines with the expert human ability to select representations: why and how19: HumanDSMachine Collaboration for Democratizing Data SciencePART 5 Evaluating Human-Like Reasoning20: Automated Commonsense Spatial Reasoning: Still a Huge Challenge21: Sampling as the human approximation to probabilistic inference22: What can the conjunction fallacy tell us about human reasoning?23: Logic-Based Robotics24: Predicting problem difficulty in chess