Doing without schema hierarchies: a recurrent connectionist approach to normal and impaired routine sequential action.

By Matthew Botvinick, David C. Plaut. 2004

370 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Social Psychology

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Citations in the corpus

Structured agents for physical construction (2019, background): “This is a natural way of expressing actions, and is similar to how humans are thought to choose actions in some behavioral domains (Ballard et al., 1997; Botvinick & Plaut, 2004).”
Reinforcement learning, efficient coding, and the statistics of natural tasks (2015, background): “com consider, neural networks [8 ,31] and graph theoretic analysis [26 ,58,66,67] appear particularly promising.”
Hierarchical Control of Cognitive Processes (2011, neutral): “For example, Schneider and Logan (2006, 2007) had subjects perform a sequence of tasks and argued that the sequence and the tasks were represented at different levels of a hierarchy but suggested that the same memory retrieval processes operated on both levels (also see Botvinick & Plaut, 2004).”
Functional Magnetic Resonance Imaging Evidence for a Hierarchical Organization of the Prefrontal Cortex (2007, neutral): “These and other properties make hierarchical frameworks common in neural and information processing models of complex or sequential action (Cooper & Shallice, 2006; Newell, 1990; Estes, 1972; Miller, Galanter, & Pribram, 1960; Lashley, 1951; although see Botvinick, 2007; Botvinick & Plaut, 2004).”
Psychology of Habit. (2016, background): “The habit system, which was originally proposed by Botvinick & Plaut (2004), selects actions in a bottom-up manner based on the current stimulus environment and on internal feedback about the network’s previous state.”
Model-based hierarchical reinforcement learning and human action control (2014, background): “What about MB-HRL? While there has been a wealth of research focusing on hierarchical structure in human behaviour [28–33], very little of this work has explicitly engaged the distinction between model-free and model-based processing (although see [34]).”
A new look at habits and the habit-goal interface. (2007, background): “In theory, models that represent routine action in terms of cognitive schemas assume that all action is organized by goals (e.g., Cooper & Shallice, 2006; Norman & Shallice, 1986), whereas models that represent routines in connectionist networks eschew a goal-mediated structure for habitual response”
Hierarchical models of behavior and prefrontal function. (2008, methodology): “Botvinick and Plaut [ 20 ] applied this model to the coffee-making task addressed by Cooper and Shallice [15], demonstrating its ability to negotiate this hierarchically structured domain.”
Hierarchically organized behavior and its neural foundations: A reinforcement-learning perspective (2008, background): “Furthermore , Ruh (2007) has demonstrated that the Botvinick and Plaut (2004) model can acquire target behaviors through RL. Understanding the relationship between this computational approach and HRL is an interesting challenge for further investigation.”
The Computational and Neural Basis of Cognitive Control: Charted Territory and New Frontiers (2014, methodology): “Thus, although this spatial differentiation of function was not computationally necessary—as demonstrated by Botvinick and Plaut (2004)—it nonetheless emerged, when the system architecture assumed a particular initial structure (see also Paine & Tani, 2005).”
Becoming syntactic. (2006, methodology): “This approach to learning and processing is present in many psychological models (e.g., Botvinick & Plaut, 2004; Gupta & Cohen, 2002; Plaut, McClelland, Seidenberg, & Patterson, 1996).”
Learning to order words: A connectionist model of heavy NP shift and accessibility effects in Japanese and English (2009, background): “Another important feature of this account is that it uses a powerful general-purpose learning algorithm (back-propagation), that has been used for modeling of non-language phenomena like making coffee or driving a car (Botvinick & Plaut, 2004; Pomerleau, 1991).”
A Usage-Based Approach to Recursion in Sentence Processing (2009, background): “Moreover, SRNs have also been shown to provide good models of nonlinguistic sequence learning (e.g., Botvinick & Plaut, 2004, 2006; Servan-Schreiber, Cleeremans, & McClelland, 1991).”
Divide and Conquer: Hierarchical Reinforcement Learning and Task Decomposition in Humans (2013, background): “Computational models have been proposed to account for how hierarchically structured procedures are represented and executed (Botvinick and Plaut, 2004; Cooper and Shallice, 2000; Schneider and Logan, 2006; Zacks et al., 2007), and how they are represented in the brain, in particular within the…”
The Acquisition of Anaphora by Simple Recurrent Networks (2013, methodology): “Sensitivity (or “lesion’’) analysis addresses this question by examining the effects of removing units or connections from the network (Plaut, McClelland & Seidenberg 1995, 1996; Botvinick & Plaut 2004; Allen & Seidenberg 1999).”