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Weekly QuEST Discussion Topics and News, 3 July

1.) We want to start this week discussing modern approaches to collaboration – specifically we’ve asked our colleague Dan Uppencamp to come in and discuss with us his Google embedding time and the tools he used (Google apps) while working in the Earth Engine group out at Mountain View. The reason we want to have this discussion is I would like to encourage us to attempt to use those tools in the development of the QuEST white paper and some of our QuEST research probably using the RDT&E network versus NIPR.
2.) The Second topic is a continuation of the discussion of implementing QuEST solutions using existing cognitive architectures and their infrastructures. This week I’m excited to discuss a recent publication by one of our colleagues Robert Patterson – Modeling Intuitive Decision Making in ACT-R. the reason I want to discuss that article is it has many of the facets we’ve been discussing associated with the proposed work of our colleague Sandy V. specifically we want to use the Patterson approach to interfacing a virtual world to ACT-R and some of their use of the existing ACT-R modules.
a. Abstract: One mode of human decision-making is considered intuitive i.e., unconscious situational pattern recognition. Implicit statistical learning, which involves the sampling of invariances from the environment and is known to involve procedural (i.e., non-declarative) memory, has been shown to be a foundation of this mode of decision making. We present an ACT-R model of implicit learning whose implementation entailed a declarative memory-based learner of the classification of example strings of an artificial grammar. The model performed very well when compared to humans. The fact that the simulation of implicit learning could not be implemented in a straightforward way via a non-declarative memory approach, but rather required a declarative memorybased implementation, suggests that the conceptualization of procedural memory in the ACT-R framework may need to be expanded to include abstract representations of statistical regularities. Our approach to the development and testing of models in ACT-R can be used to predict the development of intuitive decision-making in humans.

Weekly QuEST Discussion Topics and News 3 July

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