Exploring human-like behavior in AI: A comparative analysis of the Skyrim Herika's mod and Google Generative Agents

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abstract

Artificial Intelligence (AI) has made remarkable strides in emulating human-like behavior across various domains, ranging from video games to natural language generation. This paper investigates the extent to which AI systems can exhibit human-like behavior through a comparative analysis of two distinct implementations: the Skyrim Herika's mod and Google's generative agents.

The Skyrim Herika's mod, enhances the behavior of non-player characters (NPCs) in the popular video game "The Elder Scrolls V: Skyrim." In contrast, Google's generative agents, exemplified by models like GPT-3 and GPT-4, utilize large-scale deep learning architectures to generate human-like text based on input prompts.

Through a comparative analysis, this paper examines the approaches to achieving human-like behavior in AI. We explore the underlying technologies, methodologies, and limitations of each system. Additionally, we discuss the implications of these advancements in AI for different fields and applications.

By critically evaluating the human-like behavior exhibited by the Skyrim Herika's mod and Google generative agents, this paper contributes to a deeper understanding of the capabilities and challenges in creating AI systems that approach or simulate human-level intelligence and behavior. Moreover, it sheds light on the ethical, social, and philosophical implications of AI advancements in replicating human behaviors, offering insights into the future trajectory of AI research and development.

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