Artificial Intelligence

TURING TEST :-

The success of an intelligent behavior of a system can be measured with turing test.

Two persons and a machine to be evaluated participate in the test.out of the two persons,one plays the role of the tester. each of them sits in different rooms.the tester is unaware of who is machine and who is a human.he interrogates the questions by typing and sending them to both intelligences, to which he receives typed responses.

This test aims at fooling the tester. if the tester fails to determine machine's response from the human response,then the machine is said to be intelligent.

NATURE OF ENVIRONMENT :-

Some programs operate in the entirely ARTIFICIAL ENVIRONMENT confined to keyword input,database, computer file systems and character output on a screen.

in contrast, some software agents 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 a human.

UTILITY BASED AGENT :-

They choose actions based on a preference for each state.goals are inadequate when -

> There are conflicting goals, out of which only few can be achieved.

> Goals have some uncertainly of being achieved and you need to weigh likelihood of success against the importance of a goal.

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.

UPDATING THE STATE REQUIRES THE INFORMATION ABOUT -

How the world evolves.
How the agent's actions affect the world.

MODEL BASED REFLEX AGENTS:-

They use a model of the world to choose their actions. They maintain an internal state.

MODEL - The knowledge about how the things happen in the world.

INTERNAL STATE - It is a representation of unobserved aspects of current state depending on percept history.

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.

CONDITION-ACTION RULE -

It is a rule that maps a state (condition) to an action.

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Artificial Intelligence Educational Research Center

WHAT IS IDEAL RATIONAL AGENT ?

An ideal rational 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).

RATIONALITY:-

Rationality is nothing but status of being resonable,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.