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priya bharti
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priya bharti
Asked: April 1, 20222022-04-01T11:56:49+05:30 2022-04-01T11:56:49+05:30In: Other

Discuss Forward Versus Backward Reasoning. Describe the different approaches to Knowledge Representation in AI.

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Discuss Forward Versus Backward Reasoning. Or, Discuss Forward Reasoning vs Backward Reasoning

Describe the different approaches to Knowledge Representation in AI.

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    1. I'M ADMIN
      2022-04-07T22:39:28+05:30Added an answer on April 7, 2022 at 10:39 pm

       

      Discuss Forward Versus Backward Reasoning.

      1. The forward reasoning is data-driven approach while backward reasoning is a goal driven.
      2. The process starts with new data and facts in the forward reasoning. Conversely, backward reasoning begins with the results.
      3. Forward reasoning aims to determine the result followed by some sequences. On the other hand, backward reasoning emphasis on the acts that support the conclusion.
      4. The forward reasoning is an opportunistic approach because it could produce different results. As against, in backward reasoning, a specific goal can only have certain predetermined initial data which makes it restricted.
      5. The flow of the forward reasoning is from the antecedent to consequent while backward reasoning works in reverse order in which it starts from conclusion to incipient.
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    2. I'M ADMIN
      2022-04-07T22:42:02+05:30Added an answer on April 7, 2022 at 10:42 pm

      Knowledge representation:

      • Knowledge representation and reasoning (KR, KRR) is the part of Artificial intelligence which concerned with AI agents thinking and how thinking contributes to intelligent behavior of agents.
      • It is responsible for representing information about the real world so that a computer can understand and can utilize this knowledge to solve the complex real world problems such as diagnosis a medical condition or communicating with humans in natural language.
      • It is also a way which describes how we can represent knowledge in artificial intelligence. Knowledge representation is not just storing data into some database, but it also enables an intelligent machine to learn from that knowledge and experiences so that it can behave intelligently like a human.

       

      Following are the various types of knowledge:

       

      1. Declarative Knowledge:

      • Declarative knowledge is to know about something.
      • It includes concepts, facts, and objects.
      • It is also called descriptive knowledge and expressed in declarativesentences.
      • It is simpler than procedural language.

      2. Procedural Knowledge

      • It is also known as imperative knowledge.
      • Procedural knowledge is a type of knowledge which is responsible for knowing how to do something.
      • It can be directly applied to any task.
      • It includes rules, strategies, procedures, agendas, etc.
      • Procedural knowledge depends on the task on which it can be applied.

      3. Meta-knowledge:

      • Knowledge about the other types of knowledge is called Meta-knowledge.

      4. Heuristic knowledge:

      • Heuristic knowledge is representing knowledge of some experts in a filed or subject.
      • Heuristic knowledge is rules of thumb based on previous experiences, awareness of approaches, and which are good to work but not guaranteed.

      5. Structural knowledge:

      • Structural knowledge is basic knowledge to problem-solving.
      • It describes relationships between various concepts such as kind of, part of, and grouping of something.
      • It describes the relationship that exists between concepts or objects.
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