NDLI: Inference Through Embodied Simulation in Cognitive Robots

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Inference Through Embodied Simulation in Cognitive Robots

Content Provider	Springer Nature Link
Author	Mohan, Vishwanathan Morasso, Pietro Sandini, Giulio Kasderidis, Stathis
Copyright Year	2013
Abstract	In Professor Taylor’s own words, the most striking feature of any cognitive system is its ability to “learn and reason” cumulatively throughout its lifetime, the structure of its inferences both emerging and constrained by the structure of its bodily experiences. Understanding the computational/neural basis of embodied intelligence by reenacting the “developmental learning” process in cognitive robots and in turn endowing them with primitive capabilities to learn, reason and survive in “unstructured” environments (domestic and industrial) is the vision of the EU-funded DARWIN project, one of the last adventures Prof. Taylor embarked upon. This journey is about a year old at present, and our article describes the first developments in relation to the learning and reasoning capabilities of DARWIN robots. The novelty in the computational architecture stems from the incorporation of recent ideas firstly from the field of “connectomics” that attempts to explore the large-scale organization of the cerebral cortex and secondly from recent functional imaging and behavioral studies in support of the embodied simulation hypothesis. We show through the resulting behaviors’ of the robot that from a computational viewpoint, the former biological inspiration plays a central role in facilitating “functional segregation and global integration,” thus endowing the cognitive architecture with “small-world” properties. The latter on the other hand promotes the incessant interleaving of “top-down” and “bottom-up” information flows (that share computational/neural substrates) hence allowing learning and reasoning to “cumulatively” drive each other. How the robot learns about “objects” and simulates perception, learns about “action” and simulates action (in this case learning to “push” that follows pointing, reaching, grasping behaviors’) are used to illustrate central ideas. Finally, an example of how simulation of perception and action lead the robot to reason about how its world can change such that it becomes little bit more conducive toward realization of its internal goal (an assembly task) is used to describe how “object,” “action,” and “body” meet in the Darwin architecture and how inference emerges through embodied simulation.
Starting Page	355
Ending Page	382
Page Count	28
File Format	PDF
ISSN	18669956
Journal	Cognitive Computation
Volume Number	5
Issue Number	3
e-ISSN	18669964
Language	English
Publisher	Springer US
Publisher Date	2013-03-12
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Brain guidance Embodied simulation Small worlds Body schema Cognitive robotics Learning and reasoning DARWIN project Neurosciences Computation by Abstract Devices Artificial Intelligence (incl. Robotics) Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Cognitive Neuroscience Computer Science Applications Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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