Intelligent agent technology can be considered as a step towards the next stage of artificial intelligence. This 7new technology attempts to bridge the gap between man and machine. When bridging the man-machine gap, one of the main issues to address is how to make agents capable of autonomous actions in a dynamic environment. Inspired by human behavior, psychology and brain science, this paper presents a layered agent architecture which combines two fundamental forms of adaptation: learning and evolution. Each layer depicts the functionality of a human being making the agent better prepared to face environment dynamisms. The novel feature of the proposed architecture is, it enables the agent to evolve such that, the best action required for a given state of the environment is identified through learning rather than using a pre defined set of actions or plans.