arXiv:2606.31038v1 Announce Type: cross Abstract: For virtual humans to appear believable, they must exhibit agency and spatial awareness while interacting with their environment in ways that reflect competence and intelligence. At the core of these capabilities lies effective decision-making, which strongly shapes agent behavior. With the rapid advancement of artificial intelligence, Large Language Models (LLMs) have increasingly been explored as a mechanism to support such decision-making processes. In this work, we investigate the use of LLMs to drive decision-making in virtual humans withi
The rapid advancement of large language models (LLMs) is enabling increasingly sophisticated applications in virtual environments, pushing the boundaries of autonomous agent design.
This development indicates a significant step towards more believable and capable AI agents, crucial for simulation, training, and eventually, real-world autonomous systems.
LLMs can now drive complex decision-making processes for virtual humans, leading to more intelligent and context-aware behavior than previously achievable.
- · AI simulation companies
- · Gaming industry
- · AI agent developers
- · Defense contractors
- · Developers of custom rule-based AI
- · Companies relying on simplistic virtual agent behavior
More realistic and effective simulations across various sectors, from urban planning to emergency response, will emerge.
The improved realism of virtual agents could accelerate research into human-AI interaction and AI ethics in complex scenarios.
Sophisticated LLM-driven virtual personalities may eventually form the basis for advanced autonomous systems in diverse real-world applications.
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Read at arXiv cs.AI