ECA: An enactivist cognitive architecture based on sensorimotor modeling - Archive ouverte HAL Access content directly
Journal Articles Biologically Inspired Cognitive Architectures Year : 2013

ECA: An enactivist cognitive architecture based on sensorimotor modeling


A novel way to model an agent interacting with an environment is introduced, called an Enactive Markov Decision Process (EMDP). An EMDP keeps perception and action embedded within sensorimotor schemes rather than dissociated, in compliance with theories of embodied cognition. Rather than seeking a goal associated with a reward, as in reinforcement learning, an EMDP agent learns to master the sensorimotor contingencies offered by its coupling with the environment. In doing so, the agent exhibits a form of intrinsic motivation related to the autotelic principle (Steels, 2004), and a value system attached to interactions called interactional motivation. This modeling approach allows the design of agents capable of autonomous self-programming, which provides rudimentary constitutive autonomy—a property that theoreticians of enaction consider necessary for autonomous sense-making (e.g., Froese & Ziemke, 2009). A cognitive architecture is presented that allows the agent to autonomously discover, memorize, and exploit spatio-sequential regularities of interaction, called Enactive Cognitive Architecture (ECA). In our experiments, behavioral analysis shows that ECA agents develop active perception and begin to construct their own ontological perspective on the environment.
Fichier principal
Vignette du fichier
Georgeon0-BICA2013.pdf (707.53 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-01339190 , version 1 (13-10-2016)



Olivier Georgeon, James Marshall, Riccardo Manzotti. ECA: An enactivist cognitive architecture based on sensorimotor modeling. Biologically Inspired Cognitive Architectures, 2013, 6, pp.46-57. ⟨10.1016/j.bica.2013.05.006⟩. ⟨hal-01339190⟩
234 View
271 Download



Gmail Mastodon Facebook X LinkedIn More