Artificial Intelligence(intelligence Systems) various Components and Features

In this article, we are going to talk about Artificial Intelligence and its types and Features in an easy manner for beginners. Nowadays AI is becoming more Valuable and It has more scope for the future.

What is Intelligence?

The capacity of a system to compute, reason, recognize parallels and relationships, gain knowledge through experience, store and retrieve information from memory, solve problems, understand complex concepts, speak naturally, classify, and generalize.

Intelligence Types:

Musical intelligence:

The capacity to produce, communicate, and comprehend sound-based meanings; awareness of pitch and rhythm

Linguistic intelligence

Speaking, recognizing, and utilizing phonological (speech sounds), grammatical (grammar), and semantic (meaning) methods (meaning).

Spatial intelligence

being able to perceive visual or spatial information, alter it, and recreate visual pictures without using the objects as a reference, as well as build 3D images and move and rotate them.

Logical-mathematical intelligence

the capacity to use and comprehend relationships without action or external things. comprehending difficult and sophisticated concepts.

Bodily-Kinesthetic intelligence

control over fine and coarse motor abilities, and the ability to manage things with the entire body or just a portion of it.

Interpersonal intelligence

the capacity to distinguish between the intentions, beliefs, and feelings of another.

Intra-personal intelligence

the capacity to differentiate between one’s own thoughts, intents, and motives.

What Constitutes Intelligence?

Intelligence has no physical form. It is made up of

• Reasoning
• Learning
• Problem Solving
• Perception
• Cognitive Linguistics

Reasoning

We are able to provide a basis for judgment, decision-making, and prediction thanks to a set of processes. Generally, there are two types:

• Inductive
• Deductive

Inductive Reasoning

1. It makes precise observations before making sweeping generalizations.

2. Inductive reasoning allows for the possibility of the conclusion being untrue even though all of the premises are true.

Example: “Nita is a professor. Nita is diligent. As a result, all teachers are diligent.”

Deductive Reasoning

1. It begins with a broad assertion and considers all potential outcomes before coming to a clear, logical conclusion.

2. If something holds true for a group of objects in general, it holds true for all individuals who belong to that group.

Learning:

It is the process of learning something new through study, practice, instruction, or experience. Learning increases knowledge of the study topics. Humans, some animals, and systems using AI are all capable of learning. Learning is classified as

Stimulus-Response Learning

Learning to behave in a given way in response to certain stimuli is known as stimulus-response learning. For instance, when the doorbell rings, a dog will lift its ear.

Auditory Learning

Learning by listening and hearing is known as auditory learning. Students could listen to lectures that have been recorded as audio.

Episodic Learning

Learning through the repetition of events that one has seen or experienced is known as episodic learning. This is logical and systematic.

Relational Learning

Relational learning entails learning to distinguish between multiple stimuli based on relational characteristics rather than absolute characteristics. For instance, while cooking potatoes that were salty the prior time when you added, say, a tablespoon of salt, use “a bit less” salt this time.

Spatial Learning

Learning using visual cues like pictures, colors, maps, etc. is referred to as spatial learning. Before actually following the path, a person can, for instance, draw up a roadmap in their head.

Motor Learning

Motor learning is learning through exact muscle movement. Picking up objects, writing, etc. are a few examples.

Observational Learning

Observational learning is the process of learning by observing and copying others. The youngster, for instance, tries to learn by imitating her parent.

Perceptual Learning

Learning to recognize stimuli that one has previously seen is known as perceptual learning. Identifying and categorizing things and circumstances, for instance.

Agent and environment: what are they?

An agent is something that has sensors for sensing its surroundings and effectors for acting on it.

• A human agent has other organs, such as hands, legs, and the mouth, for effectors, in addition to sensory organs like the eyes, ears, nose, tongue, and skin, which are parallel to the sensors.
• In place of numerous motors and actuators for the effectors and cameras and infrared range finders for the sensors, there is a robotic agent.
• Encoded bit strings serve as the basis for a software agent’s actions and programs.

Agent Terminology:

Performance Measure of Agent

Agent Performance Metrics How successful an agent is is determined by the criteria.

Behavior of Agent

The agent’s conduct is whatever the agent does in response to a particular pattern of perceptions.

Percept

The agent’s perceptual inputs at a specific instance are known as percepts.

Percept Sequence

The history of everything an agent has ever perceived is known as the perceptual sequence.

Agent Function

A map from the precept sequence to action is the agent function.

What is Rationality?

• The state of being logical, sensible, and intelligent is what is meant by being rational.
• According to what the agent has perceived, rationality is concerned with anticipated behaviors and outcomes. An essential component of the reason is doing activities with the intention of learning meaningful information.

What does a rational ideal agent do?

One who is capable of doing predicted behaviors to optimize their performance measure is the ideal rational agent.

• its perceptual pattern
• Their own knowledge base

An agent’s ability to reason depends on the following factors:

• The performance metrics define success levels.
• So far, the agent’s perception sequence.
• preexisting environmental knowledge of the agent.
• The things an agent is capable of doing.

A rational agent always takes the proper action, where the proper action is defined as the action that will provide the agent the greatest chance of success in the specific perceptual sequence. The agent uses Performance Measure, Environment, Actuators, and Sensors to solve the issue (PEAS).

The Structure of Intelligent Agents

The structure of an agent can be characterized as

• Agent = Architecture + Agent Program
• Architecture = the equipment used to run agents.
• An agent program carries out an agent function.

Simple Reflex Agents:

• They only make decisions based on what they are now perceiving.
• They can only be considered rational if the proper choice is made solely based on the accepted premise.
• Their surroundings are entirely visible.

A state (condition) is mapped to an action by a rule known as the condition-action rule.

Reflex Agents Based on Models:

They make decisions about what to do based on a world model. They keep a state inside themselves.

Model

They Built a model

Internal State

Depending on the perceptual history, the internal state represents the current state’s unobserved characteristics.

Updating the state requires knowledge of

• the way the world changes.
• What impact do the agent’s deeds have on the world?

Goal-Based Agents:

They decide what they will do in order to accomplish their objectives. Since the knowledge underpinning a choice is clearly modeled in a goal-based approach, it is more adaptable than a reflex agent.

Goal — the goal is a description of the ideal circumstances.

Agents Based on Services:

Based on a preference (utility) for each state, they decide which actions to do.

When goals are insufficient.

• There are many competing objectives, but only a select number can be accomplished.
• Goals have a chance of achievement, so you must balance their importance with the possibility of accomplishment.