Human-like machine intelligence

書誌事項

Human-like machine intelligence

edited by Stephen Muggleton, Nicholas Chater

Oxford University Press, 2021

  • : hbk

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内容説明・目次

内容説明

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 chapters of this book have been authored by a mixture of UK and other international specialists. Some of the key questions addressed by the Human-Like Computing programme include how AI systems might 1) explain their decisions effectively, 2) interact with human beings in natural language, 3) learn from small numbers of examples and 4) learn with minimal supervision. Solving such fundamental problems involves new foundational research in both the Psychology of perception and interaction as well as the development of novel algorithmic approaches in Artificial Intelligence.

目次

PART 1 Human-Like Machine Intelligence 1: Human-Compatible Artificial Intelligence 2: Alan Turing and Human-Like Intelligence 3: Spontaneous communicative conventions through virtual bargaining 4: Modelling virtual bargaining using logical representation change" PART 2 Human-Like Social Cooperation 5: Mining Property-driven Graphical Explanations for Datacentric AI from Argumentation Frameworks 6: Explanation in AI systems 7: Human-Like Communication 8: Too many cooks: Coordinating multi-agent collaboration through inverse planning 9: Teaching and explanation: aligning priors between machines and humans PART 3 Human-Like Perception and Language 10: Human-Like Computer Vision 11: Apperception 12: Human-Machine Perception of Complex Signal Data 13: The sharedworkspace framework for dialogue and other cooperative joint activities 14: Beyond robotic speech: mutual benefits to cognitive psychology and artificial intelligence from the joint study of multimodal communication PART 4 Human-Like Representation and Learning 15: Human-Machine Scientific Discovery 16: Fast and slow learning in human-like intelligence 17: Interactive Learning with Mutual Explanations in Relational Domains 18: Endowing machines with the expert human ability to select representations: why and how 19: HumanDSMachine Collaboration for Democratizing Data Science PART 5 Evaluating Human-Like Reasoning 20: Automated Commonsense Spatial Reasoning: Still a Huge Challenge 21: Sampling as the human approximation to probabilistic inference 22: What can the conjunction fallacy tell us about human reasoning? 23: Logic-Based Robotics 24: Predicting problem difficulty in chess

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