503 citations · 660 across the 5 of their papers we have counts for
6 papers
Autonomous development and learning in artificial intelligence and robotics: Scaling up deep learning to human--like learning
Pierre-Yves Oudeyer
Autonomous lifelong development and learning is a fundamental capability of humans, differentiating them from current deep learning systems. However, other branches of artificial i…
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017
M. Botvinick, D. G. T. Barrett, P. Battaglia +16
We agree with Lake and colleagues on their list of key ingredients for building humanlike intelligence, including the idea that model-based reasoning is essential. However, we favo…
Building machines that adapt and compute like brains
Nikolaus Kriegeskorte, Robert M. Mok
Building machines that learn and think like humans is essential not only for cognitive science, but also for computational neuroscience, whose ultimate goal is to understand how co…
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
Samuel Ritter, David G. T. Barrett, Adam Santoro +1
Deep neural networks (DNNs) have achieved unprecedented performance on a wide range of complex tasks, rapidly outpacing our understanding of the nature of their solutions. This has…
A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G. T. Barrett +4
Relational reasoning is a central component of generally intelligent behavior, but has proven difficult for neural networks to learn. In this paper we describe how to use Relation…
Discovering objects and their relations from entangled scene representations
David Raposo, Adam Santoro, David Barrett +3
Our world can be succinctly and compactly described as structured scenes of objects and relations. A typical room, for example, contains salient objects such as tables, chairs and…