Modeling Triple-Tasking without Customized Cognitive Control

Modeling Triple-Tasking without Customized Cognitive Control Jelmer P. Borst (jpborst@ai.rug.nl) 1 Niels A. Taatgen (taatgen@cmu.edu) 1,2 Hedderik van Rijn (d.h.van.rijn@rug.nl) 1 Dept. of Artificial Intelligence, University of Groningen, The Netherlands Dept. of Psychology, Carnegie Mellon University, USA Abstract Threaded cognition is implemented in the cognitive architecture ACT-R (Anderson, 2007). ACT-R describes human cognition as a set of independent modules that interact through a central production system. For instance, it uses a visual and an aural module for perception and a motor module to interact with the world. Besides these peripheral modules, ACT-R also has a number of central cognitive modules: the procedural module that implements the central production system, the declarative memory module, the goal module, and the problem state module (sometimes referred to as imaginal module or problem representation module). All modules operate in parallel, but each module in itself can only proceed serially. Thus, the visual module can only perceive one object at a time and the memory module can only retrieve one fact at a time. A task is represented in ACT-R by the contents of the goal module and the problem state module. In the case of solving an algebra problem like ‘8x–5 = 7’, the goal module can hold for instance ‘algebra - unwinding’, while the problem state module can be used to hold the intermediate solution ‘8x = 12’ (Anderson, 2007). Thus, the goal module holds the current state of a task, while the problem state holds intermediate information necessary for performing the task. In line with the serial processing in the other modules, the goal module can only hold a single goal and the problem state module can only hold a single problem state. Threaded cognition extends ACT-R by allowing for multiple goals, and thus multiple tasks (called ‘threads’), to be kept active (Salvucci & Taatgen, 2008). While it is proposed that the goal module can hold multiple goals, the other modules are still singular, and have to be shared by the different threads. The modules are shared on a first-come- first-served basis: a thread will ‘greedily’ use a module when it needs it, but also has to let go of it ‘politely’, that is, as soon as it is done with it. The seriality of the modules results in multiple potential bottlenecks: when two threads need a module concurrently, one will have to wait for the other (Salvucci & Taatgen, 2008; Borst & Taatgen, 2007). Note that while the modules are serial in themselves, the different modules operate in parallel. In Figure 1 an example processing stream of a dual-task is shown: white boxes depict a task in which a key-press is required in reaction to a visual stimulus and grey boxes depict a task in which a vocal response is required in reaction to an auditory stimulus. The A shows interference, caused by the fact that both tasks want to use the procedural module concurrently: the aural-vocal task has to wait for the visual-manual task. Cognitive models of multitasking typically use control strategies that are customized for the tasks at hand. Salvucci and Taatgen (2008) have shown that it is possible to account for dual-tasking without using customized control: they let task properties determine how tasks are interleaved. If this is how the human cognitive system tackles multitasking, it should be possible to account in the same way for more than two tasks. In the current paper we investigate whether this approach can be extended to three concurrent tasks. Two experiments are presented: a dual- and a triple-task. We show that cognitive models without fixed control strategies cannot only account for the dual-task, but for the triple-task as well. Keywords: multitasking; threaded cognition; cognitive control, ACT-R. Introduction The ability to execute multiple tasks at the same time is an impressive feat of the human cognitive system. People can almost effortlessly combine previously unrelated tasks. To account for multitasking, most cognitive models use a customized executive (Kieras et al., 2000): a control strategy that determines how tasks are interleaved and that is specialized, and only suitable for, the tasks at hand. This seems to be at odds with the observation that people can flexibly combine tasks. A control strategy suitable for combining arbitrary tasks, a general executive, seems to be a more plausible psychological construct (e.g., Kieras et al., 2000; Salvucci, 2005). Kieras et al. implemented such a general executive, but concluded that their customized executive model accounted better for the human data. Recently, Salvucci and Taatgen proposed a new theory of multitasking, called ‘threaded cognition’ (2008; Salvucci, Taatgen, & Borst, 2009). Threaded cognition does not assume any task-specific supervisory or executive processes and can therefore combine arbitrary tasks. Salvucci and Taatgen have shown that it accounts well for dual-tasking in a number of different domains, ranging from dual-choice tasks to driving a car and using a cell phone concurrently. According to threaded cognition, human multitasking is not limited by the number of tasks that have to be performed, but only by the capacity of general cognitive resources. We will test this assumption by extending the approach to three concurrent tasks. First, we will describe a dual-tasking experiment and a well-fitting cognitive model; secondly, we will add a task to the experiment, and show that the existing model can account for the new data by just adding the new task to it. Before describing the experiments, we will briefly introduce the threaded cognition theory.