Exploring the Role of Knowledge Based System in Artificial Intelligence
Artificial Intelligence (AI) has become a prominent buzzword in recent times. AI enables machines to learn from data and make decisions like humans. Albeit the technology has progressed remarkably, AI sometimes falls short in certain circumstances. This is where Knowledge Based Systems (KBS) come into play. KBS is an AI subset that leverages domain-specific knowledge to solve problems. Let’s dive deeper into the significance of KBS in AI.
What Are Knowledge-Based Systems?
KBS is a branch of AI that extracts knowledge from a domain expert and encodes the knowledge into a computer system. The system can utilize this information to solve problems that require mastery in a specific subject matter. The knowledge can come in the form of if-then rules, decision trees or even neural networks. KBS can reason with the knowledge provided and make inferences based on it, enabling it to carry out problem-solving.
Role of KBS in AI
KBS plays a crucial role in AI, enabling systems to solve specific problems efficiently. AI systems typically require vast amounts of data to perform accurately. However, in domains where data is scarce or the problem is too specific, AI might not be the best solution. KBS, on the other hand, can solve problems in such domains. With KBS, one can encode the rules and knowledge into the system, allowing it to carry out specific problem-solving tasks.
KBS can also maintain experts’ knowledge, ensuring that it is always accessible, and prevent it from getting lost due to the expert’s retirement or death. In this way, organizations can keep their valuable intellectual property despite the experts’ absence.
Examples of KBS Applications
KBS has found numerous practical applications across different industries. One notable example of KBS application is in the medical field. Medical diagnosis requires professionals with specific domain expertise. KBS can leverage the knowledge and experience of medical professionals to make a more accurate diagnosis of diseases.
Another example of KBS application is in the financial field. KBS can be used to evaluate business risks and improve decision-making in financial institutions. KBS can be programmed with rules and regulations that financial institutions must adhere to prevent certain fraudulent activities.
Conclusion
In conclusion, KBS plays a vital role in AI. It enables AI systems to solve specific problems that require domain-specific knowledge. KBS is also instrumental in maintaining experts’ knowledge, preventing the loss of valuable intellectual property. KBS has found practical applications across different industries, from medical diagnosis to financial risk evaluation. KBS and AI are complimentary, and organizations should consider both to solve problems effectively and efficiently.
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