ERC Consolidator Grant · 2016
Abstraction and Generalisation in Human Decision-Making
Intelligent agents make good decisions in novel environments. Understanding how humans deal with novelty is a key problem in the cognitive and neural sciences, and building artificial agents that behave effectively with novel settings remains an unsolved challenge in machine learning. According to one view, humans form abstract representations that encode latent variables pertaining to the high-level structure of the environment (a “model” of the world). These abstractions facilitate generalisation of extant task and category information to novel domains. For example, an individual who can ride a bicycle, or speak Spanish, will learn more rapidly to ride a motorcycle, or speak Portuguese.…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.