Grounding Context in Embodied Cognitive Robotics.

Biological agents are context-dependent systems that exhibit behavioral flexibility. The internal and external information agents process, their actions, and emotions are all grounded in the context within which they are situated. However, in the field of cognitive robotics, the concept of context is far from being clear with most studies making little to no reference to it. The aim of this paper is to provide an interpretation of the notion of context and its core elements based on different studies in natural agents, and how these core contextual elements have been modeled in cognitive robotics, to introduce a new hypothesis about the interactions between these contextual elements. Here, global context is categorized as agent-related, environmental, and task-related context. The interaction of their core elements, allows agents to first select self-relevant tasks depending on their current needs, or for learning and mastering their environment through exploration. Second, to perform a task and continuously monitor its performance. Third, to abandon a task in case its execution is not going as expected. Here, the monitoring of prediction error, the difference between sensorimotor predictions and incoming sensory information, is at the core of behavioral flexibility during situated action cycles. Additionally, monitoring prediction error dynamics and its comparison with the expected reduction rate should indicate the agent its overall performance on executing the task. Sensitivity to performance evokes emotions that function as the driving element for autonomous behavior which, at the same time, depends on the processing of the interacting core elements. Taking all these into account, an interactionist model of contexts and their core elements is proposed. The model is embodied, affective, and situated, by means of the processing of the agent-related and environmental core contextual elements. Additionally, it is grounded in the processing of the task-related context and the associated situated action cycles during task execution. Finally, the model proposed here aims to guide how artificial agents should process the core contextual elements of the agent-related and environmental context to give rise to the task-related context, allowing agents to autonomously select a task, its planning, execution, and monitoring for behavioral flexibility.

Predictive Processing in Cognitive Robotics: A Review.

Predictive processing has become an influential framework in cognitive sciences. This framework turns the traditional view of perception upside down, claiming that the main flow of information processing is realized in a top-down, hierarchical manner. Furthermore, it aims at unifying perception, cognition, and action as a single inferential process. However, in the related literature, the predictive processing framework and its associated schemes, such as predictive coding, active inference, perceptual inference, and free-energy principle, tend to be used interchangeably. In the field of cognitive robotics, there is no clear-cut distinction on which schemes have been implemented and under which assumptions. In this letter, working definitions are set with the main aim of analyzing the state of the art in cognitive robotics research working under the predictive processing framework as well as some related nonrobotic models. The analysis suggests that, first, research in both cognitive robotics implementations and nonrobotic models needs to be extended to the study of how multiple exteroceptive modalities can be integrated into prediction error minimization schemes. Second, a relevant distinction found here is that cognitive robotics implementations tend to emphasize the learning of a generative model, while in nonrobotics models, it is almost absent. Third, despite the relevance for active inference, few cognitive robotics implementations examine the issues around control and whether it should result from the substitution of inverse models with proprioceptive predictions. Finally, limited attention has been placed on precision weighting and the tracking of prediction error dynamics. These mechanisms should help to explore more complex behaviors and tasks in cognitive robotics research under the predictive processing framework.

Total Training Volume and Muscle Soreness Parameters Performing Agonist or Antagonist Foam Rolling between Sets.

BACKGROUND: Foam rolling (FR) has become very popular in recent years; however, the practice of FR between sets of resistance training (RT) for the lower limbs needs further examination. PURPOSE: Therefore, the purpose of the present study was to examine the effect of FR for the agonists (quadriceps) and antagonists (hamstrings) between multiple sets of the leg extension on repetition maximum performance (RM), fatigue resistance index (FRI), and muscle soreness (MS). STUDY DESIGN: Quasi-experimental clinical trial. METHODS: Twenty trained men participated in this study (30.35 ± 6.56 years, 1.77 ± 0.05 cm, 87.70 ± 7.6 kg) and attended seven sessions with 48 h between sessions, (one familiarization session; two 10-RM test and retest sessions; and four experimental sessions). The four experimental sessions were performed in random order and included: agonist foam rolling (AFR), antagonist foam rolling (ANTFR), agonist/antagonist foam rolling (A/ANTFR), and traditional control (TP, without foam rolling). All sessions consisted of three sets for maximal repetitions with a 10-RM load for the leg extension. In the AFR and ANTFR sessions, there was a 120 s rest interval between sets, during which FR was done for the agonists or antagonists, respectively. In the A/ANTFR protocol, there was a 120 s rest interval between sets, during which FR was done for the agonists and antagonists. In the traditional protocol (TP), there was a 120 s passive rest interval between sets. RESULTS: Regarding the total training volume (TTV), significant differences were noted between sessions (F3,57 = 11.014; p = 0.0001). The AFR, ANTFR, and A/ANTFR sessions had significantly higher TTV versus the TP (p < 0.05). Regarding the FRI, significant differences were noted between sessions (F3,57 = 2917, p = 0.042). A significantly higher fatigue index was shown for the ANTFR and AFR sessions versus the TP (p < 0.05). Regarding the total number of repetitions, significant differences were noted between sessions (F3,57 = 11.086, p = 0.0001). The total number of repetitions was significantly higher in the A/ANTFR, ANTFR, and AFR versus the TP session (p < 0.05). MS was significantly lower in the A/ANTFR, ANTFR, and AFR sessions versus the TP session (p < 0.05). CONCLUSION: In conclusion, foam rolling between sets for the agonist or antagonist separately or in succession, resulted in greater neuromuscular performance and higher fatigue indices, as well as reducing the perception of acute muscle soreness.

Perceived Duration: The Interplay of Top-Down Attention and Task-Relevant Information.

Perception of time is susceptible to distortions; among other factors, it has been suggested that the perceived duration of a stimulus is affected by the observer's expectations. It has been hypothesized that the duration of an oddball stimulus is overestimated because it is unexpected, whereas repeated stimuli have a shorter perceived duration because they are expected. However, recent findings suggest instead that fulfilled expectations about a stimulus elicit an increase in perceived duration, and that the oddball effect occurs because the oddball is a target stimulus, not because it is unexpected. Therefore, it has been suggested that top-down attention is sometimes sufficient to explain this effect, and sometimes only necessary, with an additional contribution from saliency. However, how the expectedness of a target stimulus and its salient features affect its perceived duration is still an open question. In the present study, participants' expectations about and the saliency of target stimuli were orthogonally manipulated with stimuli presented on a short (Experiment 1) or long (Experiment 2) temporal scale. Four repetitive standard stimuli preceded each target stimulus in a task in which participants judged whether the target was longer or shorter in duration than the standards. Engagement of top-down attention to target stimuli increased their perceived duration to the same extent irrespective of their expectedness. A small but significant additional contribution to this effect from the saliency of target stimuli was dependent on the temporal scale of stimulus presentation. In Experiment 1, saliency only significantly increased perceived duration in the case of expected target stimuli. In contrast, in Experiment 2, saliency exerted a significant effect on the overestimation elicited by unexpected target stimuli, but the contribution of this variable was eliminated in the case of expected target stimuli. These findings point to top-down attention as the primary cognitive mechanism underlying the perceptual extraction and processing of task-relevant information, which may be strongly correlated with perceived duration. Furthermore, the scalar properties of timing were observed, favoring the pacemaker-accumulator model of timing as the underlying timing mechanism.

Trends in fragmentation and connectivity of Paspalum quadrifarium grasslands in the Buenos Aires province, Argentina.

BACKGROUND: Despite its wide distribution worldwide, only 4.6% of temperate grasslands are included within systems of protected areas. In Argentina, this situation is even more alarming: only 1.05% is protected. The study area (central area of the southern Salado River basin) has a large extent of grasslands of Paspalum quadrifarium (Pq) which has been target since the middle of the last century of a variety of agricultural management practices including fire burning for cattle grazing. METHODS: Five binary images of presence-absence data of Pq from a 42-year range (1974-2016) derived from a land cover change study were used as base data. Morphological Spatial Pattern Analysis (MSPA), Morphological Change Detection (MCD) and Network Connectivity Analysis (NCA) were performed to the data using Guidos Toolbox (GTB) for the estimation of habitat and connectivity dynamics of the Pq patches (fragments). RESULTS: A loss of the coverage area and habitat nuclei of this grassland was observed during the study period, with some temporal oscillation but no recovery to initial states. Additional drastic reduction in connectivity was also evident in resulting maps. The number of large Pq grassland fragments (>50 ha) decreased at beginning of the study period. Also, fragmentation measured as number of components (patches) was higher at the end of the study period. The Pq pajonal nuclei had their minimum representativeness in 2000, and recovered slightly in area in 2011, but with a significant percentage increase of smaller patches (=islets) and linear elements as bridges and branches. Large corridors (mainly edge of roads) could be observed at the end of the study period, while the total connectivity of the landscape pattern drops continuously. Statistics of links shows mean values decreasing from 1974 to 2016. On the other hand, maximum values of links decreased up to 19% in 2011, and recovered to a 54% of their original value in 2016. DISCUSSION: Pq fragmentation and habitat reduction could have an impact on the ecosystem functioning and the mobility of some species of native fauna. The connecting elements of the landscape were maintained and/or recovered in percentage in 2011 and 2016. This fact, although favoring the dispersion of the present diversity in the habitat nuclei could cause degradation by an edge effect. Part of the area has the potential to be taken as an area of research and as an example of livestock management, since it is the one that would most preserve the biodiversity of the Pq environment. On the methodological side, the use of a proved tool as GTB is useful for monitoring dynamics of a grassland-habitat fragmentation.

Parameter estimation of some epidemic models. The case of recurrent epidemics caused by respiratory syncytial virus.

The research presented in this paper addresses the problem of fitting a mathematical model to epidemic data. We propose an implementation of the Landweber iteration to solve locally the arising parameter estimation problem. The epidemic models considered consist of suitable systems of ordinary differential equations. The results presented suggest that the inverse problem approach is a reliable method to solve the fitting problem. The predictive capabilities of this approach are demonstrated by comparing simulations based on estimation of parameters against real data sets for the case of recurrent epidemics caused by the respiratory syncytial virus in children.