Precept - Agents in AI - Artificial Intelligence - Notes, Lecture notes of Artificial Intelligence

A rational agent always performs right action, where the right action means the action that causes the agent to be most successful in the given percept sequence. The problem the agent solves is characterized by Performance Measure, Environment, Actuators, and Sensors (PEAS).

Typology: Lecture notes

2015/2016

Uploaded on 03/20/2016

naachiz
naachiz 🇵🇰

4.5

(24)

34 documents

1 / 6

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
An AI system is composed of an agent and its environment. The agents act
in their environment. The environment may contain other agents.
What are Agent and Environment?
An agent is anything that can perceive
its environment through sensors and acts upon that environment
through eectors.
A human agent has sensory organs such as eyes, ears, nose, tongue and skin
parallel to the sensors, and other organs such as hands, legs, mouth, for
eectors.
A robotic agent replaces cameras and infrared range nders for the sensors,
and various motors and actuators for eectors.
A software agent has encoded bit strings as its programs and actions.
Agent Terminology
Performance Measure of Agent It is the criteria, which determines how
successful an agent is.
Behavior of Agent It is the action that agent performs after any given
sequence of percepts.
Percept It is agent’s perceptual inputs at a given instance.
Percept Sequence It is the history of all that an agent has perceived till date.
Agent Function It is a map from the precept sequence to an action.
pf3
pf4
pf5

Partial preview of the text

Download Precept - Agents in AI - Artificial Intelligence - Notes and more Lecture notes Artificial Intelligence in PDF only on Docsity!

An AI system is composed of an agent and its environment. The agents act

in their environment. The environment may contain other agents.

What are Agent and Environment?

An agent is anything that can perceive

its environment through sensors and acts upon that environment

through effectors.

  • A human agent has sensory organs such as eyes, ears, nose, tongue and skin parallel to the sensors, and other organs such as hands, legs, mouth, for effectors.
  • A robotic agent replaces cameras and infrared range finders for the sensors, and various motors and actuators for effectors.
  • A software agent has encoded bit strings as its programs and actions.

Agent Terminology

  • Performance Measure of Agent − It is the criteria, which determines how successful an agent is.
  • Behavior of Agent − It is the action that agent performs after any given sequence of percepts.
  • (^) Percept − It is agent’s perceptual inputs at a given instance.
  • Percept Sequence − It is the history of all that an agent has perceived till date.
  • Agent Function − It is a map from the precept sequence to an action.

Rationality

Rationality is nothing but status of being reasonable, sensible, and having

good sense of judgment.

Rationality is concerned with expected actions and results depending upon

what the agent has perceived. Performing actions with the aim of obtaining

useful information is an important part of rationality.

What is Ideal Rational Agent?

An ideal rational agent is the one, which is capable of doing expected

actions to maximize its performance measure, on the basis of −

  • Its percept sequence
  • Its built-in knowledge base

Rationality of an agent depends on the following four factors −

  • The performance measures , which determine the degree of success.
  • Agent’s Percept Sequence till now.
  • The agent’s prior knowledge about the environment.
  • The actions that the agent can carry out.

A rational agent always performs right action, where the right action means

the action that causes the agent to be most successful in the given percept

sequence. The problem the agent solves is characterized by Performance

Measure, Environment, Actuators, and Sensors (PEAS).

The Structure of Intelligent Agents

Agent’s structure can be viewed as −

  • Agent = Architecture + Agent Program
  • Architecture = the machinery that an agent executes on.
  • Agent Program = an implementation of an agent function.

Simple Reflex Agents

  • They choose actions only based on the current percept.
  • They are rational only if a correct decision is made only on the basis of current precept.
  • Their environment is completely observable.

Goal Based Agents

They choose their actions in order to achieve goals. Goal-based approach is

more flexible than reflex agent since the knowledge supporting a decision is

explicitly modeled, thereby allowing for modifications.

Goal − It is the description of desirable situations.

Utility Based Agents

They choose actions based on a preference (utility) for each state. Goals are

inadequate when −

  • There are conflicting goals, out of which only few can be achieved.
  • Goals have some uncertainty of being achieved and you need to weigh likelihood of success against the importance of a goal.

Nature of Environments

Some programs operate in the entirely artificial environment confined to

keyboard input, database, computer file systems and character output on a

screen.

In contrast, some software agents (software robots or softbots) exist in rich,

unlimited softbots domains. The simulator has a very detailed, complex

environment. The software agent needs to choose from a long array of

actions in real time. A softbot designed to scan the online preferences of the

customer and show interesting items to the customer works in the real as

well as an artificial environment.

The most famous artificial environment is the Turing Test environment , in

which one real and other artificial agents are tested on equal ground. This is

a very challenging environment as it is highly difficult for a software agent

to perform as well as a human.

Turing Test