Volume 21 No 1 (2023)
 Download PDF
PERFORMANCE, ENVIRONMENT, ACTUATORS, AND SENSORS MODEL TO PORTRAY AN INTELLIGENT AGENT MODEL
Gaurav D Saxena, Dr Smita Tukaram Kumbhar, D.Sasikala, Jagadeesh K Assistant Professor, Dept. of Computer Science and Engineerin, Dr. J. Jayakumar, Dr.Sonia.H.Bajaj, Dr. Amit Chauhan
Abstract
Designing intelligent agents that can do functions that are currently considered to need human intelligence is the focus of the computer science subfield known as artificial intelligence. The main objective of AI is to make computers better at learning, thinking, and perceiving. It has also been applied to the imitation or emulation of human intellect by machines. What distinguishes a computer from an artificial intelligence? An AI is composed of agents, or anything that can sense its environment. Agents employ sensors to comprehend the environment around them and actuators to act in it. For instance, computers are utilized as agents in medical diagnosis systems to process data from patient symptoms, and motors are necessary for the movement of vacuum cleaners, among other things. Using PEAS, we can better comprehend how these intelligent robots operate (Peer-to-peer Artificial Intelligence). PEAS enable collaboration between two or more persons who share a common interest. The AI agent uses the PEAS model to recognize and comprehend its surroundings. It enables precise evaluations of the agent's performance in reference to that environment. In this article, we'll examine what an intelligent agent is in more detail and talk about some of the many contexts that agents may exist in. In order to help you decide which one could be most appropriate for your project or assignment, we'll also compare their descriptions
Keywords
PEAS, PAGE, Intelligent Agent, Agent Program, Agent Architecture, Agent Types,Agent-Environment
Copyright
Copyright © Neuroquantology

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Articles published in the Neuroquantology are available under Creative Commons Attribution Non-Commercial No Derivatives Licence (CC BY-NC-ND 4.0). Authors retain copyright in their work and grant IJECSE right of first publication under CC BY-NC-ND 4.0. Users have the right to read, download, copy, distribute, print, search, or link to the full texts of articles in this journal, and to use them for any other lawful purpose.