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A Bayesian approach to the evolution of social learning
- EVOLUTION AND HUMAN BEHAVIOR
, 2012
"... There has been much interest in understanding the evolution of social learning. Investigators have tried to understand when natural selection will favor individuals who imitate others, how imitators should deal with the fact that available models may exhibit different behaviors, and how social and i ..."
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There has been much interest in understanding the evolution of social learning. Investigators have tried to understand when natural selection will favor individuals who imitate others, how imitators should deal with the fact that available models may exhibit different behaviors, and how social and individual learning should interact. In all of this work, social learning and individual learning have been treated as alternative, conceptually distinct processes. Here we present a Bayesian model in which both individual and social learning arise from a single inferential process. Individuals use Bayesian inference to combine social and nonsocial cues about the current state of the environment. This model indicates that natural selection favors individuals who place heavy weight on social cues when the environment changes slowly or when its state cannot be well predicted using nonsocial cues. It also indicates that a conformist bias should be a universal aspect of social learning.
The utility of cognitive plausibility in language acquisition modeling: Evidence from word segmentation. (Manuscript
, 2014
"... Abstract The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the mo ..."
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Abstract The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition model can aim to be cognitively plausible in multiple ways. We discuss these cognitive plausibility checkpoints in general terms, and then apply them to a case study in word segmentation, investigating a promising Bayesian segmentation strategy. We create a more cognitively plausible model of this learning strategy which uses an age-appropriate unit of perceptual representation, evaluates the model output in terms of its utility, and incorporates cognitive constraints into the inference process. Our more cognitively plausible model of the Bayesian word segmentation strategy not only yields better performance than previous implementations but also shows more strongly the beneficial effect of cognitive constraints on segmentation. One interpretation of this effect is as a synergy between the naive theories of language structure that infants may have and the cognitive constraints that limit the fidelity of their inference processes, where less accurate inference approximations are better when the underlying assumptions about how words are generated are less accurate. More generally, these results highlight the utility of incorporating cognitive plausibility more fully into computational models of language acquisition.
Reading in the Brain Revised and Extended: Response to Comments
"... Abstract: Reading in the Brain (Les neurones de la lecture, 2007) examined the origins of human reading abilities in the light of contemporary cognitive neuroscience. It argued that reading acquisition, in all cultures, recycles preexisting cortical circuits dedicated to invariant visual recognition ..."
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Abstract: Reading in the Brain (Les neurones de la lecture, 2007) examined the origins of human reading abilities in the light of contemporary cognitive neuroscience. It argued that reading acquisition, in all cultures, recycles preexisting cortical circuits dedicated to invariant visual recognition, and that the organization of these circuits imposes strong constraints on the invention and cultural evolution of writing systems. In this article, seven years later, I briefly review new experimental evidence, particularly from brain imaging studies of illiterate adults, which indicates that reading acquisition invades culturally universal cortical circuits and competes with their prior function, including mirror-invariant visual recognition and face processing. In response to my critics, I emphasize how brain plasticity and brain constraints can be reconciled within the Bayesian perspective on learning. I also discuss the importance of a newly discovered gesture system in reading and writing. Finally, I argue that there is consistent evidence for deep cross-cultural universals in writing systems, as well as for the multiple subtypes of dyslexia that are expected given the broad set of areas recruited by the reading task. It is a rare privilege for an author to see his work reviewed and dissected by a
Quantitative Standards for Absolute Linguistic Universals
, 2013
"... Absolute linguistic universals are often justified by cross-linguistic analysis: If all observed lan-guages exhibit a property, the property is taken to be a likely universal, perhaps specified in the cognitive or linguistic systems of language learners and users. In many cases, these patterns are t ..."
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Absolute linguistic universals are often justified by cross-linguistic analysis: If all observed lan-guages exhibit a property, the property is taken to be a likely universal, perhaps specified in the cognitive or linguistic systems of language learners and users. In many cases, these patterns are then taken to motivate linguistic theory. Here, we show that cross-linguistic analysis will very rarely be able to statistically justify absolute, inviolable patterns in language. We formalize two statistical methods—frequentist and Bayesian—and show that in both it is possible to find strict linguistic universals, but that the numbers of independent languages necessary to do so is gener-ally unachievable. This suggests that methods other than typological statistics are necessary to establish absolute properties of human language, and thus that many of the purported universals in linguistics have not received sufficient empirical justification.
1 A Unified Account of General Learning Mechanisms and Theory-of-Mind Development
"... Diana Meyers for helpful comments and conversations about previous versions of this article. I also thank two anonymous referees from Mind and Language. ..."
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Diana Meyers for helpful comments and conversations about previous versions of this article. I also thank two anonymous referees from Mind and Language.
AND0RETEND0LAY s
"... Many researchers have long assumed imaginative play critical to the healthy cogni-tive, social, and emotional development of children, which has important implica-tions for early-education policy and practice. But, the authors find, a careful review of the existing literature highlights a need for a ..."
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Many researchers have long assumed imaginative play critical to the healthy cogni-tive, social, and emotional development of children, which has important implica-tions for early-education policy and practice. But, the authors find, a careful review of the existing literature highlights a need for a better theory to clarify the nature of the relationship between pretend play and childhood development. In particular, they ask why children spend so much time engaging in unreal scenarios at a time when they know relatively little about the real world? The authors review the idea that children pretend because it exercises their developing ability to reason counter-factually—an ability essential for causal reasoning and learning. The authors pres-ent a look at their study in progress aimed at assessing their theory. According to the model of play they outline, imaginative play serves as an engine of learning. Such play arises out of the human capacity for causal cognition and feeds back to help develop causal-reasoning skills. Key words: Bayesian learning methods; causal learning; counterfactual reasoning; pretend play; probabilistic models Across species, the activities typically involved in play are those that will
From Coo to Code: A Brief Story of Language Development
, 2013
"... Infants begin the process of language acquisition before birth, and their brains appear specially prepared to acquire complex systems of communication. This chapter charts the child’s journey from coo to code, discussing how children find their first words in a cacophony of sound, how they determine ..."
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Infants begin the process of language acquisition before birth, and their brains appear specially prepared to acquire complex systems of communication. This chapter charts the child’s journey from coo to code, discussing how children find their first words in a cacophony of sound, how they determine what words mean, and what happens when children have variable input or learn more than one language at the same time. The journey is exciting, enlightening, and filled with surprises as we explore the myriad abilities of a child’s developing mind. 2. 5-10 keywords for indexing etc. language, language development, language acquisition, word learning, child development 3. List of 5 questions for future research What is the relationship between children’s early phonological and segmentation abilities and subsequent language acquisition? Given that we now know many of the factors associated with language development, can parents be trained to provide the kind of input that will facilitate language development if they do not do so naturally? In what ways will the advent of new neurological measures of language functioning shape the questions the field will begin to ask? Do children benefit from learning more than one language or are they hindered? What is the relationship between infants ’ abilities to form nonlinguistic concepts such as path and manner and figure and ground and their subsequent ability to express these in language? 4. Bulleted list of 10 key points to take away from the chapter
The Application of Cognitive Diagnostic Approaches via Neural Network Analysis of Serious Educational Games
"... ii DEDICATION I dedicate my dissertation work to Rebekah, Trinity my daughter, Kyler my son; I love you all. I would like to express a feeling of love and gratitude to my mother, Joyce, my grandmother Myrna and my grandfather, Theodore, without their loving guidance throughout my life I would not ha ..."
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ii DEDICATION I dedicate my dissertation work to Rebekah, Trinity my daughter, Kyler my son; I love you all. I would like to express a feeling of love and gratitude to my mother, Joyce, my grandmother Myrna and my grandfather, Theodore, without their loving guidance throughout my life I would not have come this far. I also would like to thank my brother Robert, Uncle John and Aunt Kathy for their encouragement when I needed it most. I also dedicate this dissertation to the rest of my family and friends who have supported me throughout this process. To Katherine, Mike, and Maggie who have provided friendship, feedback, and levity throughout this process and others who have pushed and pulled me to finish when I needed it. iii ACKNOWLEDGEMENTS I would like to thank my committee for their feedback. In particular my mentor Leonard Annetta who has always, without fail, guided me through my Master and Doctorate
Bayesian models of cognition revisited: Setting optimality aside and letting data drive psychological theory
"... Recent debates in the psychological literature have raised questions about what assumptions underpin Bayesian models of cognition, and what infer-ences they license about human cognition. In this paper we revisit this topic, arguing that there are two qualitatively different ways in which a Bayesian ..."
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Recent debates in the psychological literature have raised questions about what assumptions underpin Bayesian models of cognition, and what infer-ences they license about human cognition. In this paper we revisit this topic, arguing that there are two qualitatively different ways in which a Bayesian model could be constructed. If a Bayesian model is intended to license a claim about optimality then the priors and likelihoods in the model must be constrained by reference to some external criterion. A descriptive Bayesian model need not correspond to any claim that the underlying cognition is optimal or rational, and is used solely as a tool for instantiating a sub-stantive psychological theory. We present three case studies in which these two perspectives lead to different computational models and license different conclusions about human cognition. We argue that the descriptive Bayesian approach is more useful overall, especially when combined with principled tools for model evaluation and model selection. More generally we argue for the importance of making a clear distinction between the two perspectives. Considerable confusion results when descriptive models and optimal models are conflated, and if Bayesians are to avoid contributing to this confusion it is important to avoid making normative claims when none are intended.
Incorporating Cognitive Realism into Models of Early Language Acquisition
, 2013
"... Language acquisition presents a very interesting problem from a human learning standpoint. Few human-created systems are quite as complex, nor as easily and rapidly acquired as one’s native language. Over the course of a child’s first few years of life, quite a number of linguistic problems must be ..."
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Language acquisition presents a very interesting problem from a human learning standpoint. Few human-created systems are quite as complex, nor as easily and rapidly acquired as one’s native language. Over the course of a child’s first few years of life, quite a number of linguistic problems must be met and conquered, including (i) learning a sound inventory (phoneme
