A new artificial intelligence model mimics northern goshawk hunting to solve complex problems
In short: Researchers developed a new computational method called Northern Goshawk Optimization that mimics how northern goshawks hunt for prey. By modeling the bird's two-phase strategy of identifying and then chasing its target, the team created a swarm-based algorithm designed to find the best solutions to various mathematical and engineering challenges.
The study tested the algorithm against sixty-eight different objective functions and four specific engineering design problems. It was compared to eight established methods, including genetic algorithms and whale optimization. The results showed that the goshawk-inspired model performs competitively because it maintains a balance between exploring new possibilities and refining existing ones.
The study relied on computer simulations to evaluate performance. A limitation of this approach is that the results are based on mathematical models and simulated engineering problems rather than real-world physical testing.
Why it matters: Nature's hunting strategies can provide blueprints for more efficient artificial intelligence and engineering solutions.
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Sources
- Source: Research: Dehghani et al. (2021). Northern Goshawk Optimization: A New Swarm-Based Algorithm for Solving Optimization Problems. IEEE Access. · cc-by
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