Causal-Based Property Generalization

Causal-Based Property Generalization

A central question in cognitive research concerns how new properties are generalized to categories. This article introduces a model of how generalizations involve a process of causal inference in which people estimate the likely presence of the new property in individual category exemplars and then the prevalence of the property among all category members. Evidence in favor of this causal-based...

Running Head: Property Generalization as Causal Reasoning Property Generalization as Causal Reasoning

When similarity and causality compete in category-based property generalization.

Five experiments were performed to investigate the category-based generalization of nonblank properties, properties that were novel but that were attributed to existing category features with causal explanations. Experiments 1-3 tested how such explanations interact with the well-known effects of similarity on such generalizations. The results showed that when the causal explanations were used,...

Modeling Causal Generalization with Particle Filters

Psychological experiments have shown that human performance on traditional causal reasoning experiments can be greatly influenced by different pretraining and postraining conditions. In this paper we present a Bayesian theory of sequential learning that captures observed experimental results [1] . We implement our theory using the particle filter algorithm, and show that model selection and mod...

Differential Privacy as a Causal Property

We present associative and causal views of differential privacy. Under the associative view, the possibility of dependencies between data points precludes a simple statement of differential privacy’s guarantee as conditioning upon a single changed data point. However, a simple characterization of differential privacy as limiting the effect of a single data point does exist under the causal view...