Description: Bounded rationality is a concept that describes the inherent limitations in decision-making processes under uncertain environments. Unlike the notion of complete rationality, which assumes that individuals have access to all information and can process it optimally, bounded rationality acknowledges that people operate under cognitive and informational constraints. This means that instead of seeking the best possible solution, individuals tend to look for satisfactory solutions that are ‘good enough’ given the circumstances. This approach is based on the idea that human information processing capacity is limited, leading them to simplify complex problems and use heuristics or general rules to make decisions. Bounded rationality is particularly relevant in contexts where uncertainty and complexity are high, such as in economics, psychology, and artificial intelligence. This concept has influenced the development of decision-making models where agents must learn to make optimal decisions based on past experiences, often in environments where information is incomplete or noisy.
History: The term ‘bounded rationality’ was introduced by economist Herbert Simon in the 1950s. Simon argued that due to human cognitive limitations and the complexity of the world, people cannot make decisions in a completely rational manner. His work in this field earned him the Nobel Prize in Economics in 1978. Over the years, the concept has evolved and been integrated into various disciplines, including psychology, economics, and game theory.
Uses: Bounded rationality is used in various fields, such as behavioral economics, where it studies how cognitive limitations affect economic decisions. It is also applied in artificial intelligence, especially in decision-making models, where agents must learn to make optimal decisions in uncertain environments. Additionally, it is used in management and organizational decision-making to understand how leaders make decisions under pressure and with limited information.
Examples: An example of bounded rationality in everyday life is choosing a restaurant. Instead of researching all available restaurants, a person might choose one that was recommended by a friend, considering this option to be ‘good enough.’ In the field of artificial intelligence, an agent making decisions in a simulation may not explore all possible strategies but instead relies on past experiences to make quick and effective decisions.
