Agent Environment Interaction

Agent-environment interaction research focuses on developing artificial agents capable of effectively learning and operating within complex, dynamic environments. Current research emphasizes improving agent capabilities through techniques like reinforcement learning, often enhanced by large language models (LLMs) for improved planning and decision-making, and active inference for modeling sustainable resource management. This field is crucial for advancing artificial intelligence in areas such as autonomous systems, robotics, and resource management, driving progress towards more robust and adaptable AI agents.