.png){kind=icon}
返回
Meta-learning in active inference
.png){kind=icon}
PRE
AI
DOI：10.1017/S0140525X24000074.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Psychologists and neuroscientists extensively rely on computational models for studying and analyzing the human mind. Traditionally, such computational models have been hand designed by expert researchers. Two prominent examples are cognitive architectures and Bayesian models of cognition. Although the former requires the specification of a fixed set of computational structures and a definition of how these structures interact with each other, the latter necessitates the commitment to a particular prior and a likelihood function that - in combination with Bayes' rule - determine the model's behavior. In recent years, a new framework has established itself as a promising tool for building models of human cognition: the framework of meta-learning. In contrast to the previously mentioned model classes, meta-learned models acquire their inductive biases from experience, that is, by repeatedly interacting with an environment. However, a coherent research program around meta-learned models of cognition is still missing to date. The purpose of this article is to synthesize previous work in this field and establish such a research program. We accomplish this by pointing out that meta-learning can be used to construct Bayes-optimal learning algorithms, allowing us to draw strong connections to the rational analysis of cognition. We then discuss several advantages of the meta-learning framework over traditional methods and reexamine prior work in the context of these new insights.
Keyword:
Bayesian inference
cognitive modeling
meta-learning
neural networks
rational analysis
期刊
IF:
13.7
论文数:
1.6W
被引数:
1.2W
机构
引用论文
Recent advances in the application of predictive coding and active inference models within clinical neuroscience预测编码和主动推理模型在临床神经科学中应用的最新进展
OAAI
.png){kind=icon}
OAAI分享收藏分享收藏Whatever next? Predictive brains, situated agents, and the future of cognitive science接下来呢？预测大脑，定位代理和认知科学的未来
OAAI
OAAI分享收藏
查看更多内容