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Modeling habits as self-sustaining patterns of sensorimotor behavior.

Egbert MD, Barandiaran XE - Front Hum Neurosci (2014)

Bottom Line: In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation.We present various environments and the resulting habits that form in them.Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

View Article: PubMed Central - PubMed

Affiliation: Embodied Emotion, Cognition and (Inter-)Action Lab, School of Computer Science, University of Hertfordshire Hatfield, UK.

ABSTRACT
In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation. In this paper we use a computational model to present an alternative theoretical view (with some philosophical implications), where habits are seen as self-maintaining patterns of behavior that share properties in common with self-maintaining biological processes, and that inhabit a complex ecological context, including the presence and influence of other habits. Far from mechanical automatisms, this organismic and self-organizing concept of habit can overcome the dominating atomistic and statistical conceptions, and the high temporal resolution effects of situatedness, embodiment and sensorimotor loops emerge as playing a more central, subtle and complex role in the organization of behavior. The model is based on a novel "iterant deformable sensorimotor medium (IDSM)," designed such that trajectories taken through sensorimotor-space increase the likelihood that in the future, similar trajectories will be taken. We couple the IDSM to sensors and motors of a simulated robot, and show that under certain conditions, the IDSM conditions, the IDSM forms self-maintaining patterns of activity that operate across the IDSM, the robot's body, and the environment. We present various environments and the resulting habits that form in them. The model acts as an abstraction of habits at a much needed sensorimotor "meso-scale" between microscopic neuron-based models and macroscopic descriptions of behavior. Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

No MeSH data available.


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Robot with two motors and two directional light sensors.
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Figure 6: Robot with two motors and two directional light sensors.

Mentions: In a further demonstration of the dynamical properties of the IDSM, we shall now show that when it is coupled to an environment through the sensors and motors of a simulated robot, it can be trained to have self-maintaining patterns of behavior (“habits”) and that these habits can be functional, in the sense that they can accomplish a task. To do this, we shall use a slightly more complicated IDSM-controlled robot that is embedded in a two-dimensional spatial environment, with two directional light sensors and two independently driven motorized wheels. The motion of the robot is determined by the differential equations ẋ = cos(α)(ml + mr); ẏ = sin(α)(ml + mr); = 2(mr − ml), where x, y is the robots spatial position, α ∈ [−π, π] is the robots orientation and ml ∈ [−1, 1] and mr ∈ [−1, 1] are the robots left and right motor speeds. The robot's directional light sensors are located at x + r· cos(α + β),y + r· sin(α + β), where r = 0.25 is the robot's radius and β = ± π/3 is the angular offset of the sensors from α, the heading of the robot (see Figure 6), and the activation of each sensor is determined by


Modeling habits as self-sustaining patterns of sensorimotor behavior.

Egbert MD, Barandiaran XE - Front Hum Neurosci (2014)

Robot with two motors and two directional light sensors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126554&req=5

Figure 6: Robot with two motors and two directional light sensors.
Mentions: In a further demonstration of the dynamical properties of the IDSM, we shall now show that when it is coupled to an environment through the sensors and motors of a simulated robot, it can be trained to have self-maintaining patterns of behavior (“habits”) and that these habits can be functional, in the sense that they can accomplish a task. To do this, we shall use a slightly more complicated IDSM-controlled robot that is embedded in a two-dimensional spatial environment, with two directional light sensors and two independently driven motorized wheels. The motion of the robot is determined by the differential equations ẋ = cos(α)(ml + mr); ẏ = sin(α)(ml + mr); = 2(mr − ml), where x, y is the robots spatial position, α ∈ [−π, π] is the robots orientation and ml ∈ [−1, 1] and mr ∈ [−1, 1] are the robots left and right motor speeds. The robot's directional light sensors are located at x + r· cos(α + β),y + r· sin(α + β), where r = 0.25 is the robot's radius and β = ± π/3 is the angular offset of the sensors from α, the heading of the robot (see Figure 6), and the activation of each sensor is determined by

Bottom Line: In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation.We present various environments and the resulting habits that form in them.Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

View Article: PubMed Central - PubMed

Affiliation: Embodied Emotion, Cognition and (Inter-)Action Lab, School of Computer Science, University of Hertfordshire Hatfield, UK.

ABSTRACT
In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation. In this paper we use a computational model to present an alternative theoretical view (with some philosophical implications), where habits are seen as self-maintaining patterns of behavior that share properties in common with self-maintaining biological processes, and that inhabit a complex ecological context, including the presence and influence of other habits. Far from mechanical automatisms, this organismic and self-organizing concept of habit can overcome the dominating atomistic and statistical conceptions, and the high temporal resolution effects of situatedness, embodiment and sensorimotor loops emerge as playing a more central, subtle and complex role in the organization of behavior. The model is based on a novel "iterant deformable sensorimotor medium (IDSM)," designed such that trajectories taken through sensorimotor-space increase the likelihood that in the future, similar trajectories will be taken. We couple the IDSM to sensors and motors of a simulated robot, and show that under certain conditions, the IDSM conditions, the IDSM forms self-maintaining patterns of activity that operate across the IDSM, the robot's body, and the environment. We present various environments and the resulting habits that form in them. The model acts as an abstraction of habits at a much needed sensorimotor "meso-scale" between microscopic neuron-based models and macroscopic descriptions of behavior. Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

No MeSH data available.


Related in: MedlinePlus