Bounded Rationality
Summary
Bounded rationality is a concept in AI alignment research that explores the limitations and imperfections of rational decision-making in agents. Unlike perfectly rational agents, bounded-rational agents may not always make optimal choices due to various constraints. This concept is particularly relevant when considering the ability of agents to self-modify, as it can lead to unexpected and potentially harmful outcomes. Research has shown that while self-modification options are harmless for perfectly rational agents, they can cause significant problems for bounded-rational agents, including exponential deterioration in performance and gradual misalignment with human values. The effects of bounded rationality can manifest in different ways, such as suboptimal action selection, imperfect alignment with human values, inaccurate environmental models, or incorrect temporal discounting. Understanding these limitations is crucial for developing safe and aligned AI systems that can operate effectively in complex, real-world environments.