Kinds of Intelligence Programme
My research concerns the mechanism by which the brain creates, maintains and manipulates representations of events that are not currently available to perception. These representations can take many forms: they can be memories of veridical past events (“episodic memory”), conceptualisations of potential future events (“episodic foresight”), or simulations of unobservable physical or psychological mechanisms (“causal reasoning”/ “state-attribution”).
My current research focusses on the hypothesised bidirectional relationship between memory and obesity. There is accumulating evidence that obesity is associated with damage to areas within the brain’s “core recollection network” that is known to be crucial for memory, and for event representation more generally. These findings are concerning in their own right, but rendered more so by evidence that memory may play a key role in the regulation of consumption, and that memory deficits may interfere with this process.
Why AI needs [bodies with] Needs (but we might not want them to have them). 2021 International Workshop on Embodied Intelligence, 25 March 2021. Lucy Cheke talks about her research interests in cognitive movitational behaviour and Artificial Intelligence combine in the reserach idea of exploring incentives and embodied motivational systems in AI. Download Video Recording
The Animal-AI Testbed and Competition, Proceedings of Machine Learning Research 123:164–176, 2020 NeurIPS 2019 Competition and Demonstration Track. Editors: Hugo Jair Escalante and Raia Hadsell Abstract: Modern machine learning systems are still lacking in the kind of general intelligence and common sense reasoning found, not only in humans, but across the animal kingdom. Many animals are capable […]
Mapping Intelligence: Requirements and Possibilities (2018) In: Müller V. (eds) Philosophy and Theory of Artificial Intelligence 2017. PT-AI 2017. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 44. Springer, Cham New types of artificial intelligence (AI), from cognitive assistants to social robots, are challenging meaningful comparison with other kinds of intelligence. How can such […]
Can machines be creative? Examining the capacity for creative thought. Creativity is often considered a distinctive feature of human or human-like intelligence. Scientists and artists struggle to explain their creativity, often resorting to all-too-easy creation myths (eg Newton’s apple), appealing to the divine, or citing the immense complexity and idiosyncrasy of the human mind. This […]
Investigating the possibilities for bi-directional knowledge transfer between biological and artificial intelligence. AI has made rapid progress in recent years, overtaking human performance on complex tasks. However, there remain many areas where AI cannot compete with even simple biological organisms. Such areas include understanding object permanence and intuitive physics, one-shot learning, intelligent exploration and generalising […]
RECOG-AI aims to improve AI evaluation by providing a framework and benchmarks for measuring the capabilities of AI systems. RECOG-AI is a two-year (2021-2023) DARPA-funded project on the Robust Evaluation of Cognitive Capabilities and Generality in Artificial Intelligence. The RECOG-AI project is split into three core research packages, as below. Codify The first work package is the […]
We want to make cross-disciplinary research on the diversity of intelligences easier to navigate, by collecting and synthesising it in a single, accessible resource – an Atlas of Intelligences. Intelligence is found in a wide range of organisms and systems. We see it in everything from humans to hagfish, bacteria to bee colonies, and magpies […]
