Alejandra Ciria | Universidad Nacional Autónoma de México (original) (raw)

Papers by Alejandra Ciria

Frontiers in Neurorobotics

Biological agents are context-dependent systems that exhibit behavioral flexibility. The internal... more 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 perfo...

2020 Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2020

How do cognitive agents decide which is the relevant information to learn and how goals are selec... more How do cognitive agents decide which is the relevant information to learn and how goals are selected to gain this knowledge? Cognitive agents need to be motivated to perform any action. We discuss that emotions arise when differences between expected and actual rates of progress toward a goal are experienced. Therefore, the tracking of prediction error dynamics has a tight relationship with emotions. Here, we suggest that the tracking of prediction error dynamics allows an artificial agent to be intrinsically motivated to seek new experiences but constrained to those that generate reducible prediction error. We present an intrinsic motivation architecture that generates behaviors towards self-generated and dynamic goals and that regulates goal selection and the balance between exploitation and exploration through multi-level monitoring of prediction error dynamics. This new architecture modulates exploration noise and leverages computational resources according to the dynamics of the overall performance of the learning system. Additionally, it establishes a possible solution to the temporal dynamics of goal selection. The results of the experiments presented here suggest that this architecture outperforms intrinsic motivation approaches where exploratory noise and goals are fixed and a greedy strategy is applied.

Advanced Topics on Computer Vision, Control and Robotics in Mechatronics, 2018

Cognitive robotics has focused its attention on the design and construction of artificial agents ... more Cognitive robotics has focused its attention on the design and construction of artificial agents that are able to perform some cognitive task autonomously through the interaction of the agent with its environment. A central issue in these fields is the process of learning. In its attempt to imitate cognition in artificial agents, cognitive robotics has implemented models of cognitive processes proposed in areas such as biology, psychology, and neurosciences. A novel methodology for the control of autonomous artificial agents is the paradigm that has been called neuro-robotics or embedded neural cultures, which aims to embody cultures of biological neurons in artificial agents. The present work is framed in this paradigm. In this chapter, simulations of an autonomous learning process of an artificial agent controlled by artificial action potential neural networks during an obstacle avoidance task were carried out. The implemented neural model was introduced by Izhikevich (2003); this model is capable of reproducing abrupt changes in the membrane potential of biological neurons, known as action potentials. The learning strategy is based on a multimodal association process where the synaptic weights of the networks are modified using a Hebbian rule. Despite the growing interest generated by artificial action potential neural networks, there is little research that implements these models for learning and the control of autonomous agents. The present work aims to fill this gap in the literature and at the same time, serve as a guideline for the design of further experiments for in vitro experiments where neural cultures are used for robot control.

Recent technological advances have provided the manufacturing industry with precise and robust ma... more Recent technological advances have provided the manufacturing industry with precise and robust machines that perform better than their human counterparts in tiresome and tedious jobs. Likewise, robots can perform high precision tasks including in hazardous environments. However, a new area of research in robotics has emerged in the last decades, namely cognitive robotics. The main interest in this area is the study of cognitive processes in humans and their implementation and modeling in artificial agents. In cognitive robotics, the use of robots as platforms, in the study of cognition, is the best-suited mechanism as they naturally interact with their environment and learn through this interaction. Following these ideas, in these works, two low-level cognitive tasks are modeled and implemented in an artificial agent. Based on the ecological framework of perception, in the first experiment, an agent learns its body map. In the second experiment, the agent acquires a distance-to-obst...

Differences between sexes in the subjective estimation of time when performing tasks of verbal fl... more Differences between sexes in the subjective estimation of time when performing tasks of verbal fluency and mental rotation of 3-D images were studied in this research. 240 Mexican college students were divided in six groups; one male and one female group for each condition: Verbal, Spatial, and Control tasks. Subjects were asked to perform their corresponding task during two minutes which they had to estimate by themselves. No significant time estimation differences (p = .6913) between sexes were found when performing the verbal fluency task. However, significant time estimation differences (p = .0265) between the male and the female group were found with the mental rotation task. In addition, no significant time estimation differences between sexes were observed as for verbal fluency skills (p = .8265) and mental rotation (p = .4506). Results are discussed in terms of the evidence that shows that men have a higher activation in the right parietal region when performing mental rotat...

Int. J. Comb. Optim. Probl. Informatics, 2021

Frontiers in Psychology, 2019

Neural Computation, 2021

Predictive processing has become an influential framework in cognitive sciences. This framework t... more 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 cognitiv...

Adaptive Behavior, 2018

Embodied Cognitive Robotics focuses its attention on the design of artificial agents capable of p... more Embodied Cognitive Robotics focuses its attention on the design of artificial agents capable of performing cognitive tasks autonomously. A central issue in this consists in studying process by which agents learn through interaction with their environment. Embodied Cognitive Robotics aims to implement models of cognitive processes coming from Cognitive Sciences. The guidelines in this research area are a direct response to the shortcomings of Classical Artificial Intelligence, where high-level tasks and behaviors were studied. This article describes the work carried out in the Cognitive Robotics Laboratory at the Universidad Autónoma del Estado de Morelos (UAEM). Our work is based on the concept of low-level sensorimotor schemes coded by Internal Models, thus falling as a matter of course within the tenets of Embodied Cognition, particularly with the idea that cognition must be understood as occurring in agents that have a body with which they interact in a specific environment. It i...

We present an intrinsic motivation architecture that generates behaviors towards self-generated a... more We present an intrinsic motivation architecture that generates behaviors towards self-generated and dynamic goals and that regulates goal selection and the balance between exploitation and exploration through multi-level monitoring of prediction error dynamics. This architecture modulates exploration noise and leverages computational resources according to the dynamics of the overall performance of the learning system. Results show that this architecture outperforms intrinsic motivation approaches where exploratory noise and goals are fixed. We suggest that the tracking of prediction error dynamics allows an artificial agent to be intrinsically motivated to seek new experiences but constrained to those that generate reducible prediction error. We argue about the potential relationship between emotional valence and rates of progress toward a goal.

Perception of time is susceptible to distortions; among other factors, it has been suggested that... more 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.