Learning task structure from video examples for workflow tracking and authoring

Author(s):  
Nils Petersen ◽  
Didier Stricker
Keyword(s):  
2018 ◽  
Author(s):  
Christina Bejjani ◽  
Tobias Egner

Humans are characterized by their ability to leverage rules for classifying and linking stimuli to context-appropriate actions. Previous studies have shown that when humans learn stimulus-response associations for two-dimensional stimuli, they implicitly form and generalize hierarchical rule structures (task-sets). However, the cognitive processes underlying structure formation are poorly understood. Across four experiments, we manipulated how trial-unique images mapped onto responses to bias spontaneous task-set formation and investigated structure learning through the lens of incidental stimulus encoding. Participants performed a learning task designed to either promote task-set formation (by “motor-clustering” possible stimulus-action rules), or to discourage it (by using arbitrary category-response mappings). We adjudicated between two hypotheses: Structure learning may promote attention to task stimuli, thus resulting in better subsequent memory. Alternatively, building task-sets might impose cognitive demands (for instance, on working memory) that divert attention away from stimulus encoding. While the clustering manipulation affected task-set formation, there were also substantial individual differences. Importantly, structure learning incurred a cost: spontaneous task-set formation was associated with diminished stimulus encoding. Thus, spontaneous hierarchical task-set formation appears to involve cognitive demands that divert attention away from encoding of task stimuli during structure learning.


2021 ◽  
Author(s):  
Francesco Poli ◽  
Tommaso Ghilardi ◽  
Rogier B. Mars ◽  
Max Hinne ◽  
Sabine Hunnius

Infants learn to navigate the complexity of the physical and social world at an outstanding pace, but how they accomplish this learning is still unknown. Recent advances in human and artificial intelligence research propose that a key feature to achieve quick and efficient learning is meta-learning, the ability to make use of prior experiences to optimize how future information is acquired. Here we show that 8-month-old infants successfully engage in meta-learning within very short timespans. We developed a Bayesian model that captures how infants attribute informativity to incoming events, and how this process is optimized by the meta-parameters of their hierarchical models over the task structure. We fitted the model using infants’ gaze behaviour during a learning task. Our results reveal that infants do not simply accumulate experiences, but actively use them to generate new inductive biases that allow learning to proceed faster in the future.


2020 ◽  
Author(s):  
Adam Eichenbaum ◽  
Jason M. Scimeca ◽  
Mark D’Esposito

AbstractHumans can draw insight from previous experiences in order to quickly adapt to novel environments that share a common underlying structure. Here we combine functional imaging and computational modeling to identify the neural systems that support the discovery and transfer of hierarchical task structure. Human subjects completed multiple blocks of a reinforcement learning task that contained a global hierarchical structure governing stimulus-response action mapping. First, behavioral and computational evidence showed that humans successfully discover and transfer the hierarchical rule structure embedded within the task. Next, analysis of fMRI BOLD data revealed activity across a frontal-parietal network that was specifically associated with the discovery of this embedded structure. Finally, activity throughout a cingulo-opercular network and in caudal frontal cortex supported the transfer and implementation of this discovered structure. Together, these results reveal a division of labor in which dissociable neural systems support the learning and transfer of abstract control structures.


1975 ◽  
Vol 36 (2) ◽  
pp. 561-562
Author(s):  
Jack R. Haynes

A serial-learning task composed of eight trigrams scaled by proximity analysis was given to two groups. The same items were used for both groups, but the order was different. The trigrams were in a random order for one group while the other group had their list structured according to radex theory. The structured list produced faster learning with fewer errors than the random order.


2020 ◽  
Author(s):  
Tricia X.F. Seow ◽  
Redmond O’Connell ◽  
Claire M. Gillan

AbstractIndividuals with higher levels of compulsivity exhibit poorer performance on tasks that require model-based planning but the underlying causes have yet to be established. Here, we sought to determine whether these deficits stem from impoverished action-outcome relational knowledge (i.e. issues building an accurate model of the world) and/or an inability to translate models into action. 192 participants performed a two-step reinforcement learning task with concurrent EEG recordings. We found that representations of task-relevant action-outcome associations reflected in reaction time and parietal-occipital alpha-band power were stronger in individuals whose decisions were more model-based, and critically, were weaker in those high in compulsivity. At the time of choice, mid-frontal theta power, a general marker of cognitive control, was also negatively associated with compulsivity, but not model-based planning. These data suggest that model-based planning deficits in compulsive individuals may arise from failures in building an accurate model of the world.


2002 ◽  
Vol 61 (3) ◽  
pp. 139-151 ◽  
Author(s):  
Céline Darnon ◽  
Céline Buchs ◽  
Fabrizio Butera

When interacting on a learning task, which is typical of several academic situations, individuals may experience two different motives: Understanding the problem, or showing their competences. When a conflict (confrontation of divergent propositions) emerges from this interaction, it can be solved either in an epistemic way (focused on the task) or in a relational way (focused on the social comparison of competences). The latter is believed to be detrimental for learning. Moreover, research on cooperative learning shows that when they share identical information, partners are led to compare to each other, and are less encouraged to cooperate than when they share complementary information. An epistemic vs. relational conflict vs. no conflict was provoked in dyads composed by a participant and a confederate, working either on identical or on complementary information (N = 122). Results showed that, if relational and epistemic conflicts both entailed more perceived interactions and divergence than the control group, only relational conflict entailed more perceived comparison activities and a less positive relationship than the control group. Epistemic conflict resulted in a more positive perceived relationship than the control group. As far as performance is concerned, relational conflict led to a worse learning than epistemic conflict, and - after a delay - than the control group. An interaction between the two variables on delayed performance showed that epistemic and relational conflicts were different only when working with complementary information. This study shows the importance of the quality of relationship when sharing information during cooperative learning, a crucial factor to be taken into account when planning educational settings at the university.


Author(s):  
Tom Beckers ◽  
Uschi Van den Broeck ◽  
Marij Renne ◽  
Stefaan Vandorpe ◽  
Jan De Houwer ◽  
...  

Abstract. In a contingency learning task, 4-year-old and 8-year-old children had to predict the outcome displayed on the back of a card on the basis of cues presented on the front. The task was embedded in either a causal or a merely predictive scenario. Within this task, either a forward blocking or a backward blocking procedure was implemented. Blocking occurred in the causal but not in the predictive scenario. Moreover, blocking was affected by the scenario to the same extent in both age groups. The pattern of results was similar for forward and backward blocking. These results suggest that even young children are sensitive to the causal structure of a contingency learning task and that the occurrence of blocking in such a task defies an explanation in terms of associative learning theory.


2014 ◽  
Author(s):  
Shawn Ell ◽  
Steve Hutchinson ◽  
Lauren Hawthorne ◽  
Lauren Szymula ◽  
Shannon K. McCoy

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