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Development of Artificial Intelligent Skills and Techniques in Agricultural Robotics
Objectives: This analysis paper mainly focuses on the development of cognitive architecture where the agents at different levels exhibit different levels of thinking and on the acquisition of smart sensor motor skills which is known as Construction Skill Tree (CST). Methods/Statistical Analysis: These concepts are implemented through simulation by using prolog programming language. This simulation is an imitation of the operation of real world fruit picking robot system over time. It includes the discovery of one’s own body, including its structure and dynamics. This includes the acquisition of associated cognitive skills such as self and non-self-distinction. Finding: The obtained simulation results can be given by designing and implementing the Construction Skill tree Implementation Architecture (CSIA). The design of CSIA provides faster skill acquisition. Hence it is called CSIA, the CSIA has a five layer and first four layers are single agent environment. Improvement/Application: The proposed cognitive architecture has collections of agents that work together for reaching predefined goal. In CSIA these contains reflexive, reactive, deliberative, thinking and meta-thinking layer.
Agent, Construction Skill tree Implementation Architecture (CSIA), Cognitive Architecture, Smart Fruit Picking Robots.
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