The Behavioral and brain sciences
Jun 19, 2020
The commentaries address our view of abstraction, our ontology of abstract entities, and our account of predictive cognition as relying on relatively concrete simulation or relatively abstract theory-based inference. These responses revisit classic q...
The Behavioral and brain sciences
Nov 28, 2019
Brette contends that the neural coding metaphor is an invalid basis for theories of what the brain does. Here, we argue that it is an insufficient guide for building an artificial intelligence that learns to accomplish short- and long-term goals in a...
The Behavioral and brain sciences
Nov 24, 2016
Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and boa...
The Behavioral and brain sciences
Jan 1, 2018
We argue that a radically increased emphasis on (bounded) optimality can contribute to cognitive science by supporting prediction. Bounded optimality (computational rationality), an idea that borrowed from artificial intelligence, supports a priori b...
The Behavioral and brain sciences
Jan 1, 2017
We propose an alternative approach to "deep" learning that is based on computational ecologies of structurally diverse artificial neural networks, and on dynamic associative memory responses to stimuli. Rather than focusing on massive computation of ...
The Behavioral and brain sciences
Jan 1, 2017
Machines that learn and think like people should simulate how people really think in their everyday lives. The field of artificial intelligence originally traveled down two roads, one of which emphasized abstract, idealized, rational thinking and the...
The Behavioral and brain sciences
Jan 1, 2017
Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous lear...
The Behavioral and brain sciences
Jan 1, 2017
Lake et al. suggest that current AI systems lack the inductive biases that enable human learning. However, Lake et al.'s proposed biases may not directly map onto mechanisms in the developing brain. A convergence of fields may soon create a correspon...
The Behavioral and brain sciences
Jan 1, 2017
We comment on ways in which Lake et al. advance our understanding of the machinery of intelligence and offer suggestions. The first set concerns animal-level versus human-level intelligence. The second concerns the urgent need to address ethical issu...
The Behavioral and brain sciences
Jan 1, 2017
Lake et al. offer a timely critique on the recent accomplishments in artificial intelligence from the vantage point of human intelligence and provide insightful suggestions about research directions for building more human-like intelligence. Because ...