Introduction to Artificial Intelligence

introduction to artificial intelligence

Artificial Intelligence

AI can be that the mechanism to include human intelligence into machines through a group of rules(algorithm).

AI could be a combination of two words: “Artificial” meaning something not real which is created by humans or non-natural things and “Intelligence” meaning the flexibility to grasp or think accordingly.

These are the 2 terms which may be together are often accustomed define the something which isn’t real which is formed by humans yet intelligent.AI has mainly specializing in the three methods for obtained the chances of maximum efficiency.

  • Learning
  • Reasoning
  • Self-correction

Goals of computing

Following are the most goals of Artificial Intelligence:

1. Replicate human intelligence

2. Solve Knowledge-intensive tasks

3. An intelligent connection of perception and action

4. Building a machine which might perform tasks that needs human intelligence such as:

  • Proving a theorem
  • Playing chess
  • Plan some surgical procedure  
  • Driving a car in traffic

Types of AI :

  • Artificial Narrow Intelligence (ANI)
  • Artificial General Intelligence (AGI)
  • Artificial Super Intelligence (ASI)

Types of AI Agents

  • Simple Reflex Agent
  • Model-based reflex agent
  • Goal-based agents
  • Utility-based agent
  • Learning agent

1.Simple Reflex agent:

  • The Simple reflex agents are the only agents.
  • These agents only achieve the fully observable environment. The Simple reflex agent doesn’t consider any a part of percepts history during their decision and action process.
  • The Simple reflex agent works on Condition-action rule, which suggests it maps this state to action.
  • Like a space Cleaner agent, it works providing there’s dirt within the room.
  • Problems for the straightforward reflex agent design approach:
  • They have very limited intelligence. 
  • They don’t have knowledge of non-perceptual parts of this state.
  • Mostly too big to get and to store. Not adaptive to changes within the environment.

2. Model-based reflex agent

  • The Model-based agent can add a partially observable environment, and track matters.
  • Internal State: it’s a representation of the present state supported percept history.
  • These agents have the model, “which is knowledge of the world” and supported the model they perform actions.

3. Goal-based agents

  • The knowledge of the present state environment isn’t always sufficient to make a decision for an agent to what to try and do.
  • The agent must know its goal which describes desirable situations.They choose an action, so they’ll achieve the goal.
  • These agents may should consider an extended sequence of possible actions before deciding whether the goal is achieved or not.

4. Utility-based agents

  • These agents are just like the goal-based agent but provide an additional component of utility measurement which makes them different by providing a measure of success at a given state.
  • Utility-based agent act based not only goals but also the most effective thanks to achieve the goal.
  • The Utility-based agent is helpful when there are multiple possible alternatives, and an agent must choose so as to perform the simplest action.

5. Learning Agents

  • A learning agent in AI is that the sort of agent which may learn from its past experiences, or it’s learning capabilities.
  • It starts to act with basic knowledge and so ready to act and adapt automatically through learning.

a. Learning element: it’s chargeable for making improvements by learning from environment

b. Critic: Learning element takes feedback from critic which describes that how well the agent is doing with reference to a hard and fast performance standard.

c. Performance element: it’s answerable for selecting external action

d. Problem generator: This component is to blame for suggesting actions that may result in new and informative experiences.

Hence, learning agents are ready to learn, analyze performance, and appearance for brand new ways to boost the performance.

Why Artificial Intelligence?

Before Learning about AI, we must always know that what’s the importance of AI and why should we learn it.

  • With the assistance of AI, you’ll be able to create such software or devices which may solve real-world problems very easily and with accuracy like health issues, marketing, traffic issues, etc.
  • With the assistance of AI, you’ll create your personal virtual Assistant, like Cortana, Google Assistant, Siri, etc.
  • With the assistance of AI, you’ll be able to build such Robots which may add an environment where survival of humans are often in danger.

Advantages of Artificial Intelligence

  • High Accuracy with less errors: AI machines or systems are prone to less errors and high accuracy as it takes decisions as per pre-experience or information.
  • High-Speed: AI systems can be of very high-speed and fast-decision making, because of that AI systems can beat a chess champion in the Chess game.
  • High reliability: AI machines are highly reliable and can perform the same action multiple times with high accuracy.
  • Useful for risky areas: AI machines can be helpful in situations such as defusing a bomb, exploring the ocean floor, where to employ a human can be risky.
  • Digital Assistant: AI can be very useful to provide digital assistant to the users such as AI technology is currently used by various E-commerce websites to show the products as per customer requirement.
  • Useful as a public utility: AI can be very useful for public utilities such as a self-driving car which can make our journey safer and hassle-free, facial recognition.

Disadvantages of Artificial Intelligence

Every technology has some disadvantages, and the same goes for Artificial intelligence.

  • High Cost: The hardware and software requirement of AI is very costly as it requires lots of maintenance to meet current world requirements.
  • No feelings and emotions: AI machines can be an outstanding performer, but still it does not have the feeling so it cannot make any kind of emotional attachment
  • Increase dependency on machines: With the increment of technology, people are getting more dependent on devices and hence they are losing their mental capabilities.
  • No Original Creativity: As humans are so creative and can imagine some new ideas but still AI machines cannot beat this power of human intelligence and cannot be creative and imaginative.
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