![]() On the general level, intuitive physics, naïve physics or folk physics (terms used here synonymously) is the universally similar human perception of fundamental physical phenomena, or an intuitive (innate) understanding all humans have about objects in the physical world. ![]() By mimicking the brain’s biological neural networks, computational models that rapidly learn, improve and apply their subsequent learning to new tasks in unstructured real-world environments can undoubtedly play a major role in enabling future software and hardware (robotic) systems to make better inferences from smaller amounts of training data. Such neural networks (deep learning networks in particular) can be generally characterized by collectively-performing neural-network-style models organized in a number of layers of representation, followed by a process of gradually refining their connection strengths as more data is introduced. The overview is structured around intuitive physics techniques using cognitive (neural) networks with the objective to harness our understanding of how artificial agents may emulate aspects of human (infants’) cognition into a general-purpose physics simulator for a wide range of everyday judgments and tasks. A particular context of intuitive physics explored herein is the infants’ innate understanding of how inanimate objects persist in time and space or otherwise follow principles of persistence, inertia and gravity-the spatio-temporal configuration of physical concepts-soon after birth, occurring via the domain-specific perceptual causality (Caramazza & Shelton, 1998). More recently, cognitive psychology and artificial intelligence (AI) researchers have been motivated by the need to explore the concept of intuitive physics in infants’ object perception skills and understand whether further theoretical and practical applications in the field of artificial intelligence could be developed by linking intuitive physics’ approaches to the research area of AI-by building autonomous systems that learn and think like humans.
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