The propositional nature of human associative learning

The past 50 years have seen an accumulation of evidence suggesting that associative learning depends oil high-level cognitive processes that give rise to propositional knowledge. Yet, many learning theorists maintain a belief in a learning mechanism in which links between mental representations are formed automatically. We characterize and highlight the differences between the propositional and link approaches, and review the relevant empirical evidence. We conclude that learning is the consequence of propositional reasoning processes that cooperate with the unconscious processes involved in memory retrieval and perception. We argue that this new conceptual framework allows many of the important recent advances in associative learning research to be retained, but recast in a model that provides a firmer foundation for both immediate application and future research

The Bayesian sampler : generic Bayesian inference causes incoherence in human probability

Human probability judgments are systematically biased, in apparent tension with Bayesian models of cognition. But perhaps the brain does not represent probabilities explicitly, but approximates probabilistic calculations through a process of sampling, as used in computational probabilistic models in statistics. Naïve probability estimates can be obtained by calculating the relative frequency of an event within a sample, but these estimates tend to be extreme when the sample size is small. We propose instead that people use a generic prior to improve the accuracy of their probability estimates based on samples, and we call this model the Bayesian sampler. The Bayesian sampler trades off the coherence of probabilistic judgments for improved accuracy, and provides a single framework for explaining phenomena associated with diverse biases and heuristics such as conservatism and the conjunction fallacy. The approach turns out to provide a rational reinterpretation of “noise” in an important recent model of probability judgment, the probability theory plus noise model (Costello & Watts, 2014, 2016a, 2017; Costello & Watts, 2019; Costello, Watts, & Fisher, 2018), making equivalent average predictions for simple events, conjunctions, and disjunctions. The Bayesian sampler does, however, make distinct predictions for conditional probabilities and distributions of probability estimates. We show in 2 new experiments that this model better captures these mean judgments both qualitatively and quantitatively; which model best fits individual distributions of responses depends on the assumed size of the cognitive sample

Investigating Properties of Phonotactic Knowledge Through Web-Based Experimentation

The goal of this dissertation is to advance the state of the art of research in constraint-based phonotactics. It takes a two-pronged approach: a technological contribution intended to facilitate future research, and experiments which seek to shed light on high-level questions about the properties of phonotactic models that can guide the development of theoretical work. The technological contribution is a software package called Speriment which allows experimenters to create and run experiments over the internet without advanced programming techniques. This software is particularly well suited to the kinds of experiments often run in phonotactic research, but can also be used for experiments in other domains of linguistics and the social sciences. It is hoped that this software will make it faster and easier to conduct phonotactic and other experiments as well as encourage experimenters to increase the reproducibility and transparency of their research. The experiments presented here address questions that assume constraint-based phonotactic frameworks, but that do not rely on particular theories of the content of the constraint set. That is, they apply to constraint-based frameworks for theories of phonotactics, with the first study seeking to distinguish between two such frameworks, a linear version of Harmonic Grammar and Maximum Entropy, while the second investigates whether phonotactic knowledge is independent of knowledge of phonological alternations. These coarse-grained questions about phonotactic knowledge on how pieces of phonotactic knowledge interact with each other and with another part of the grammar are intended to add to the groundwork on which phonotactic models and models of all phonological knowledge are built. Their findings have implications for which constraint-based frameworks should be used for future theories and how these theories can be reliably tested

A Plea for Minimally Biased Empirical Philosophy

Naturalistic philosophers rely on literature search and review in a number of ways and for different purposes. Yet this article shows how processes of literature search and review are likely to be affected by widespread and systematic biases. A solution to this problem is offered here. Whilst the tradition of systematic reviews of literature from scientific disciplines has been neglected in philosophy, systematic reviews are important tools that minimize bias in literature search and review and allow for greater reproducibility and transparency. If naturalistic philosophers wish to reduce bias in their research, they should then supplement their traditional tools for literature search and review by including systematic methodologies

A Plea for Minimally Biased Empirical Philosophy

Naturalistic philosophers rely on literature search and review in a number of ways and for different purposes. Yet this article shows how processes of literature search and review are likely to be affected by widespread and systematic biases. A solution to this problem is offered here. Whilst the tradition of systematic reviews of literature from scientific disciplines has been neglected in philosophy, systematic reviews are important tools that minimize bias in literature search and review and allow for greater reproducibility and transparency. If naturalistic philosophers wish to reduce bias in their research, they should then supplement their traditional tools for literature search and review by including systematic methodologies