Object-Process Methodology as an Alternative to Human Factors Task Analysis

Objective We define and demonstrate the use of OPM-TA—a model-based task analysis (TA) framework that uses object-process methodology (OPM) ISO 19450 as a viable alternative to traditional TA techniques. Background A variety of different TA methods exist in human factors engineering, and several of them are often applied successively for a broad task representation, making it difficult to follow. Method Using OPM-TA, we modeled how an International Space Station (ISS) astronaut would support extravehicular activities using the existing robotic arm workstation with a new control panel and an electronic procedure system. The modeling employed traditional TA methods and the new OPM-TA approach, enabling a comparison between them. Results While the initial stages of modeling with OPM-TA follow those of traditional TA, OPM-TA modeling yields an executable and logically verifiable model of the entire human–robot system. Both OPM’s hierarchical set of diagrams and the equivalent, automatically generated statements in a subset of natural language text specify how objects and processes relate to each other at increasingly detailed levels. The graphic and textual OPM modalities specify the system’s architecture, which enables its function and benefits its users. To verify the model logical correctness model, we executed it using OPM’s simulation capability. Conclusion OPM-TA was able to unify traditional TA methods and expand their capabilities. The formal yet intuitive OPM-TA approach fuses and extends traditional TA methods, which are not amenable to simulation. It therefore can potentially become a widely used means for TA and human–machine procedure development and testing.

Dissociating the Neural Correlates of Planning and Executing Hierarchical Task Sets

Task processing and task representation, two facets of cognitive control, are both supported by lateral frontal cortex (LFC). However, processing and representation have largely been investigated separately, so it is unknown if they are distinguishable aspects of control or if they are complementary descriptions of the same mechanism. Here, we explored this by combining a hierarchical task mapping with a pre-cueing procedure. Participants made match/non-match judgments on features of pairs of stimuli. Cues presented at the start of each trial indicated the judgment domain (spatial/non-spatial), the response hand, both, or neither, giving variable amounts of information to the subject at each time point in the trial. Our results demonstrated that regions throughout LFC supported task processing, indicated by an influence of time point on their BOLD activity levels. A subset of regions in left caudal LFC also supported task representation, indicated by an interaction between time point and cue information; we termed this subgroup the "CuexTime" group. This interaction effect was not seen in the remaining LFC regions, which only showed a main effect of time consistent with involvement in task processing; we termed this subgroup the "Time" group. These results suggest that task representation is one component of task processing, confined to the "CuexTime group" in left caudal LFC, while other regions in our task support other aspects of task processing. We further conducted an exploratory investigation of connectivity between regions in the "CuexTime" and "Time" groups and their potential relationship to networks that support distinct cognitive control functions.

Polynomial-Time in PDDL Input Size: Making the Delete Relaxation Feasible for Lifted Planning

Polynomial-time heuristic functions for planning are commonplace since 20 years. But polynomial-time in which input? Almost all existing approaches are based on a grounded task representation, not on the actual PDDL input which is exponentially smaller. This limits practical applicability to cases where the grounded representation is "small enough". Previous attempts to tackle this problem for the delete relaxation leveraged symmetries to reduce the blow-up. Here we take a more radical approach, applying an additional relaxation to obtain a heuristic function that runs in time polynomial in the size of the PDDL input. Our relaxation splits the predicates into smaller predicates of fixed arity K. We show that computing a relaxed plan is still NP-hard (in PDDL input size) for K>=2, but is polynomial-time for K=1. We implement a heuristic function for K=1 and show that it can improve the state of the art on benchmarks whose grounded representation is large.

Cognitive Capacity, Representation, and Instruction

The central argument of the present article is that Cognitive Psychology’s problems in dealing with the concept of “cognitive capacity” is intimately linked with Cognitive Psychology’s long-lasting failure of coming to terms with the concept of “representation” in general, and “task representation” in particular. From this perspective, the role of instructions in psychological experiments is emphasised. It is argued that both a careful conceptual analysis of instruction-induced task representations as well as an experimental variation of instructions promises to broaden our understanding of the role of task representations as a determinant of limited cognitive capacity.

Neural representation of abstract task structure during generalization

Cognitive models in psychology and neuroscience widely assume that the human brain maintains an abstract representation of tasks. This assumption is fundamental to theories explaining how we learn quickly, think creatively, and act flexibly. However, neural evidence for a verifiably generative abstract task representation has been lacking. Here, we report an experimental paradigm that requires forming such a representation to act adaptively in novel conditions without feedback. Using functional magnetic resonance imaging, we observed that abstract task structure was represented within left mid-lateral prefrontal cortex, bilateral precuneus and inferior parietal cortex. These results provide support for the neural instantiation of the long-supposed abstract task representation in a setting where we can verify its influence. Such a representation can afford massive expansions of behavioral flexibility without additional experience, a vital characteristic of human cognition.

Effect of task complexity on ipsilateral motor response programming to physically presented and imagined stimuli

It is unclear whether task representation generated in imagery simulates performance demands in reacting to stimuli. This study investigated whether perceptual and motor control processes used to react to unpredictable stimuli and initiate an ipsilateral movement were replicated during imagery. Fifty-nine undergraduate students ( Mage = 27.01 years, SD = 8.30) completed 30 simple, two-choice congruent and two-choice incongruent ipsilateral finger–foot movement trials in response to a physically presented or imagined stimulus. The results appear to indicate that participants were reacting to imagined and actual stimuli, as the ipsilateral finger–foot programming rule was maintained and reaction time initially slowed as task difficulty increased. These findings support theoretical similarities between imagery and physical performance of reaction tasks, with imagers generating and reacting to unpredictable stimuli. Slower imagery performance than physical performance on the two-choice incongruent task may indicate that task complexity is limited during imagery. Variation in results between the imagery and physical conditions potentially supports that imagers were able to react to the imagined stimulus. However, exploratory processes used to react to stimuli were not replicated during imagery. The present findings have potentially significant implications for the functional and applied use of imagery for skill acquisition.