On the adaptive function of children's and adults' false memories

Recent research has shown that memory illusions can successfully prime both children’s and adults’ performance on complex, insight-based problems (compound remote associates tasks or CRATs). The current research aimed to clarify the locus of these priming effects. Like before, Deese/Roediger-McDermott (DRM) lists were selected to prime subsequent CRATs such that the critical lures were also the solution words to a subset of the CRATs participants attempted to solve. Unique to the present research, recognition memory tests were used and participants were either primed during the list study phase, during the memory test phase, or both. Across two experiments, primed problems were solved more frequently and significantly faster than unprimed problems. Moreover, when participants were primed during the list study phase, subsequent solution times and rates were considerably superior to those produced by those participants who were simply primed at test. Together, these are the first results to show that false-memory priming during encoding facilitates problem solving in both children and adults

Simulating Context Effects in Problem Solving with AMBR

This paper presents a computer simulation of context effects on problem solving with AMBR --- a model of human analogy-making. It demonstrates how perceiving some incidental objects from the environment may change the way the problem is being solved. It also shows that the timing of this perception is important: while the context element may have crucial influence during the initial stages of problem solving it has virtually no effect during the later stages. The simulation also explores the difference between an explicit hint condition where the focus of attention is drawn towards a context situation which is analogous to the target problem and an implicit context condition where an arbitrary object from the environment makes us remind an old episode

Dynamics and Automaticity of Context: A Cognitive Modeling Approach

AI and psychological approaches to context are contrasted and the dynamic and automatic nature of the continuous context change in human cognition is emphasized. A dynamic theory of context is presented which defines context as the dynamic state of human mind. It describes the interaction between memory, perception, and reasoning in forming context as well as how they are influenced by context. A general cognitive architecture, DUAL, is presented that implements the mechanisms of context formation and accounts for the context-sensitivity of human cognition. A model of human problem solving, AMBR, has been built upon the DUAL architecture and the simulation experiments performed with it produce data that are coherent with experimental data on human problem solving

A Model Architecture for Mental Imagery

Kaiser A, Schenck W, Möller R. A Model Architecture for Mental Imagery. In: Kokinov B, Karmiloff-Smith A, Nersessian NJ, eds. European Perspectives on Cognitive Science. New Bulgarian University Press; 2011