C-tests revisited: back and forth with complexity

We explore the aggregation of tasks by weighting them using a difficulty function that depends on the complexity of the (acceptable) policy for the task (instead of a universal distribution over tasks or an adaptive test). The resulting aggregations and decompositions are (now retrospectively) seen...

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Detalles Bibliográficos
Autor: Hernández-Orallo, José|||0000-0001-9746-7632
Tipo de recurso: capítulo de libro
Fecha de publicación:2015
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/64413
Acceso en línea:https://riunet.upv.es/handle/10251/64413
Access Level:acceso abierto
Palabra clave:Intelligence evaluation
Artificial intelligence
C-tests
Algorithmic information theory
Universal psychometrics
Agent response curve
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Descripción
Sumario:We explore the aggregation of tasks by weighting them using a difficulty function that depends on the complexity of the (acceptable) policy for the task (instead of a universal distribution over tasks or an adaptive test). The resulting aggregations and decompositions are (now retrospectively) seen as the natural (and trivial) interactive generalisation of the C-tests.