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pro vyhledávání: '"Kinghorn, Paul F"'
An open problem in artificial intelligence is how systems can flexibly learn discrete abstractions that are useful for solving inherently continuous problems. Previous work in computational neuroscience has considered this functional integration of d
Externí odkaz:
http://arxiv.org/abs/2409.01066
An open problem in artificial intelligence is how systems can flexibly learn discrete abstractions that are useful for solving inherently continuous problems. Previous work has demonstrated that a class of hybrid state-space model known as recurrent
Externí odkaz:
http://arxiv.org/abs/2408.10970
The ability to invent new tools has been identified as an important facet of our ability as a species to problem solve in dynamic and novel environments. While the use of tools by artificial agents presents a challenging task and has been widely iden
Externí odkaz:
http://arxiv.org/abs/2311.03893
Predictive Coding Networks (PCNs) aim to learn a generative model of the world. Given observations, this generative model can then be inverted to infer the causes of those observations. However, when training PCNs, a noticeable pathology is often obs
Externí odkaz:
http://arxiv.org/abs/2208.07114
In cognitive science, behaviour is often separated into two types. Reflexive control is habitual and immediate, whereas reflective is deliberative and time consuming. We examine the argument that Hierarchical Predictive Coding (HPC) can explain both
Externí odkaz:
http://arxiv.org/abs/2109.00866