Good enough strategies favor animal survival

Good enough strategies favor animal survival

Survival Strategies

A new study shows that using a ‘good enough’ strategy to complete a task could have advantages over striving for perfection. Researchers from the Howard Hughes Medical Institute in the US sought to challenge traditional methods of animal research, where diverse behaviors in activities such as mating, hunting, or evading predators are typically compared to some optimized method. Using theoretical algorithms and models, the researchers examined a simple and widely used method where animals (such as mice) choose between various options to get a reward.

They developed many alternative strategies for the task, aiming to analyze the difference between good enough and perfect. “Many of these strategies are ones we would have never dreamed up as possible ways of solving this task, but they do work well, so it’s entirely possible that animals could also be using them,” said physicist Ann Hermundstad. “They give us a new vocabulary for understanding behavior.”

The researchers formulated more than a quarter of a million approaches – or ‘programs’ – that fall between perfect and random approaches.

Some of these programs achieved the end goals while using fewer resources, suggesting they might be preferable.

Good enough strategies in animal behavior

They also found that despite such diverse approaches, they could all be understood in terms of algorithmic ‘mutations,’ where strategies evolved from one another with tiny tweaks in their steps.

Around 4,000 of the programs described were ‘good enough’ to get results, with 90 percent doing something a little different from the optimal strategy. This is important because it shows that even significant deviations from a perfect plan can still succeed while providing some variation that could be useful in other tasks. Veering away from an optimal strategy may negatively impact the outcome of the primary focus. Still, this compromise is offset when multiple tasks are considered -– a situation more accurately reflects everyday life.

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Suppose you are thinking about an animal not being a specialist optimized to solve just one problem but rather a generalist who solves many issues. In that case, this is a new way to study that,” said physicist and computer scientist Tzuhsuan Ma. For researchers, the findings could demonstrate why an animal might not always take what seems to be the best route from A to B or provide a better understanding of how success in a goal is weighed with the resources available. “As soon as you release yourself from being perfect, you will be surprised by just how many ways there are to solve a problem,” the researchers concluded.


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