As Artificial General Intelligence systems evolve toward human-level intelligence, autonomous decision-making becomes a foundational capability—empowering AGI to act, adapt, and learn independently in complex environments. This session at the AGI Conference 2026 will delve into the theories, architectures, and real-world implementations of autonomous decision-making in AGI, exploring the balance between autonomy, reliability, and alignment with human goals.

Key focus areas include:

• Decision Theory for AGI: Exploring how AGI systems model choices under uncertainty, evaluate long-term outcomes, and reason about utility functions.

• Self-Improving AGI Agents: Understanding systems that can adapt their strategies over time, update goals based on feedback, and engage in continual learning.

• Autonomous Agents in the Real World: Case studies of AGI-driven agents making real-time decisions in dynamic domains such as robotics, autonomous vehicles, finance, and defense.

• Trade-offs in Autonomy vs. Oversight: Discussing frameworks to determine when human-in-the-loop controls are essential and when AGI can operate independently.

• Neural-Symbolic and Hybrid Decision Architectures: Combining data-driven learning with symbolic reasoning for more robust and transparent AGI decisions.

Attendees will engage with cutting-edge research and practical demonstrations that highlight both the opportunities and the challenges in designing AGI systems capable of safe, scalable, and context-aware autonomous decision-making.

Join global experts at the Artificial Intelligence Conference 2026 to explore the path toward building AGI systems that think and act with autonomous intelligence—redefining what machines can achieve on their own.