The function of the octopus in its environment

further understand this concept, according to Zylinski & How (2012) various species such as octopuses show extraordinary problem-solving abilities. Octopuses can navigate mazes, open jars, and use tools, displaying advanced cognitive skills shaped by their distinctive neurological structure (Zylinski & How, 2012). These behaviors, driven by their decentralized nervous system, provide support that these cephalopods allow for advanced and flexible behaviors that could influence new computational models and learning algorithms in artificial intelligence challenge our understanding of intelligence and learning, offering an evident contrast to mammalian models. Research conducted by Kuba et al. (2010) further provides evidence that octopuses can engage in observational learning, suggesting a level of cognitive processing that may align more with complex vertebrates. (Kuba et al., 2010). By studying these mechanisms, we can uncover alternative learning strategies that could be applied to artificial intelligence and robotics, where decentralized control systems might mimic octopus problem-solving.

Examining these views, I support the concept that researchers should expand their scope to include species with unique adaptations. According to Emery & Clayton (2004), understanding other species with various abilities that show remarkable cognitive abilities despite having different brain structures than humans, provides insight into intelligence and innovation in unpredictable environments (Emery & Clayton, 2004). However, there are arguments against the direct applicability of animal studies to human cognition. For instance, Salwiczek et al. (2012) found that while certain fish can outperform primates in specific tasks, these tasks are highly context-

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