Robotic Behavior based on Formal Grammars

Robotic Behavior based on Formal Grammars

J.L. Briseno

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M.A. Jimnez

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G. Olague

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1 Center for Scientific Research and Higher Education of Ensenada

GJCST Volume 18 Issue D2

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The objective of our study was to evaluate, in a population of Togolese People Living With HIV(PLWHIV), the agreement between three scores derived from the general population namely the Framingham score, the Systematic Coronary Risk Evaluation (SCORE), the evaluation of the cardiovascular risk (CVR) according to the World Health Organization.

Formal grammars, studied by N. Chomsky for the definition of equivalence with languages and models of computing, have been a useful tool in the development of compilers, programming languages, natural language processing, automata theory, etc. The words or symbols of these formal languages can denote deduced actions that correspond to specific behaviors of a robotic entity or agent that interacts with an environment. The primary objective of this paper pretend to represent and generate simple behaviors of artificial agents. Reinforcement learning techniques, grammars, and languages, as defined based on the model of the proposed system were applied to the typical case of the ideal route on the problem of artificial ant. The application of such techniques proofs the viability of building robots that might learn through interaction with the environment.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

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Not applicable for this article.

J.L. Briseno. 2018. \u201cRobotic Behavior based on Formal Grammars\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 18 (GJCST Volume 18 Issue D2): .

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GJCST Volume 18 Issue D2
Pg. 1- 6

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Classification

GJCST-D Classification: I.2.9

Submission ReceivedDecember 16, 2017
RevisedDecember 16, 2017
Peer Review Double Blind
Handling Editor
Accepted January 1, 2018
Published January 15, 2018

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v1.2

Issue date

September 29, 2018

Language

English

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Total Score: 103

Country: Unknown

Subject: Global Journal of Computer Science and Technology - D: Neural & AI

Authors: J.L. Briseno, M.A. Jimnez, G. Olague (PhD/Dr. count: 0)

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Publish Date: 2018 09, Sat

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Total Views: 5755

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