Theory of mind as inverse reinforcement learning
J Jara-Ettinger - Current Opinion in Behavioral Sciences, 2019 - Elsevier
We review the idea that Theory of Mind—our ability to reason about other people's mental
states—can be formalized as inverse reinforcement learning. Under this framework …
states—can be formalized as inverse reinforcement learning. Under this framework …
Bayesian brains without probabilities
AN Sanborn, N Chater - Trends in cognitive sciences, 2016 - cell.com
Bayesian explanations have swept through cognitive science over the past two decades,
from intuitive physics and causal learning, to perception, motor control and language. Yet …
from intuitive physics and causal learning, to perception, motor control and language. Yet …
The best game in town: The reemergence of the language-of-thought hypothesis across the cognitive sciences
Mental representations remain the central posits of psychology after many decades of
scrutiny. However, there is no consensus about the representational format (s) of biological …
scrutiny. However, there is no consensus about the representational format (s) of biological …
Human-level concept learning through probabilistic program induction
People learning new concepts can often generalize successfully from just a single example,
yet machine learning algorithms typically require tens or hundreds of examples to perform …
yet machine learning algorithms typically require tens or hundreds of examples to perform …
Hypothesis search: Inductive reasoning with language models
Inductive reasoning is a core problem-solving capacity: humans can identify underlying
principles from a few examples, which can then be robustly generalized to novel scenarios …
principles from a few examples, which can then be robustly generalized to novel scenarios …
A model of conceptual bootstrapping in human cognition
To tackle a hard problem, it is often wise to reuse and recombine existing knowledge. Such
an ability to bootstrap enables us to grow rich mental concepts despite limited cognitive …
an ability to bootstrap enables us to grow rich mental concepts despite limited cognitive …
A rational account of pedagogical reasoning: Teaching by, and learning from, examples
Much of learning and reasoning occurs in pedagogical situations—situations in which a
person who knows a concept chooses examples for the purpose of helping a learner …
person who knows a concept chooses examples for the purpose of helping a learner …
Compositional abilities emerge multiplicatively: Exploring diffusion models on a synthetic task
Modern generative models exhibit unprecedented capabilities to generate extremely
realistic data. However, given the inherent compositionality of real world, reliable use of …
realistic data. However, given the inherent compositionality of real world, reliable use of …
Bayesian fundamentalism or enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition
The prominence of Bayesian modeling of cognition has increased recently largely because
of mathematical advances in specifying and deriving predictions from complex probabilistic …
of mathematical advances in specifying and deriving predictions from complex probabilistic …