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Volume - 3 | Issue - 2 | december 2024

Exploring Artificial Intelligence PEAS Framework for Enhanced Decision-Making
Rama Bansal  , Shikha Gupta, Kishori Ravi Shankar, Arundhati  183  430
Pages: 397-409
Cite this article
Bansal, Rama, Shikha Gupta, Kishori Ravi Shankar, and Arundhati. "Exploring Artificial Intelligence PEAS Framework for Enhanced Decision-Making." Recent Research Reviews Journal 3, no. 2 (2024): 397-409
Published
02 December, 2024
Abstract

An agent can refer to any device employed as a sensor to detect environmental elements and entities, providing responses based on that information. The cycle of agents can include perception, action, processing, and performance, while the environment around us is populated with agents such as temperature sensors, CCTV cameras, mobile phones, and more. Humans, software, and robots around us also function as AI agents. Using artificial intelligence we can create advanced systems with human-like behaviour. This research study represents a comprehensive view of existing literature and an analysis of methods designed to enhance Artificial Intelligence decision-making possibilities. By studying the facts and details of PEAS models of AI, a better idea can be gained on how AI can make decisions similar to human intelligence. This study includes a literature review of some related research. Objective of this study is to discuss the framework, elements, and challenges of the PEAS model in Artificial Intelligence and to simulate the model of control agents for traffic light control systems, its framework with entities and parameters, and limitations.

Keywords

AI Agent PEAS Traffic Light Control Sensors

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