> Enter reinforcement learning, a theoretical framework that helps explain how the rewards and punishments of life get translated into effective behavior. It doesn’t matter if it’s monkeys responding to squirts of juice or rats jonesing for pellets or humans plying the stock market: The algorithms of reinforcement learning neatly describe our decisions. The persuasive power of reinforcement is why we give kindergartners gold stars and professionals a monetary bonus: Nothing influences outcomes like a bit of positive feedback. Furthermore, neuroscientists have identified several mechanisms in the cortex that seem to obey these computational principles. It’s an incredibly elegant link between the software of mind and the hardware of brain. > What is the effect of the change in behaviour on players’ performance? Intuitively, increasing the frequency of attempting a 3pt after made 3pts and decreasing it after missed 3pts makes sense if a made/missed 3pts predicted a higher/lower 3pt percentage on the next 3pt attempt. Surprizingly [sic], our data show that the opposite is true. The 3pt percentage immediately after a made 3pt was 6% lower than after a missed 3pt. Moreover, the difference between 3pt percentages following a streak of made 3pts and a streak of missed 3pts increased with the length of the streak. These results indicate that the outcomes of consecutive 3pts are anticorrelated. > What’s the larger lesson? It turns out that professional athletes over-generalize from their most recent actions and outcomes. They modify their behavior based on the result of a single shot, even though the success of the shot was shaped by unpredictable forces (a butterfly flapping its wings in Tokyo, etc.) and depended on situational details that are unlikely to be repeated. (Perhaps the defender was momentarily distracted, or failed to run around the screen.) As the scientists note, “The behavior of basketball players shows the limitations of learning from reinforcement, especially in a complex environment such as a basketball game.” http://www.wired.com/wiredscience/2011/1.....ent-fails/