Two marks Questions with Answers

Two Marks Questions with Answers

Q.1 Define an agent.

Ans.: An agent is anything (a program, a machine assembly) that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators.

Q.2 Define rational agent.

Ans.: A rational agent is agent which always works as per the expected performance. It is a agent who always acts perfectly as per the expectation. It tries to maximize expected behavioural performance.

Q.3 Give the general model of learning agent.

Ans.: Learning agent model have four component -

1) Learning Element - Which is responsible for making improvements.

2) Performance Elements - Which is responsible for selecting external actions.

3) Critic - It tells how agent is doing. (that is it evaluates output).

4) Problem Generator - It responsible for suggesting actions.

Q.4 What is role of agent program?

Ans.: Agent program is important and central part of agent system. It drives the agent, which means that it analyzes date and provides probable actions agent could take.

An agent program is internally implemented as agent function.

An agent program takes input as the current percept from the sensor and return an action to the effectors (Actuator).

Q.5 List down the characteristics of intelligent agent.

Ans.: 1) The IA must learn and improve through interaction with the environment.

2) The IA must adapt online and in the real time situation.

3) The IA must accommodate new problem solving rules incrementally.

4) The IA must have memory which must exhibit storage and retrieval capacities.

Q.6 Define abstraction.

Ans.: In artificial intelligence the abstraction is commonly used to account for the use of various levels in details in a given representation language or the ability to change from one level to another while preserving useful properties. Abstraction has been mainly studied in problem solving, theorem proving, knowledge representation and machine learning. In such context, abstraction is defined as mapping between formalism that reduces the computational complexity of the task in question.

Q.7 State the concept of rationality.

Ans.: Rationality is the capacity to generate maximally successfull behaviour given the available information. Rationality also indicates the capacity to compute the perfectly rational decision given the initially available information. The capacity to select the optimal combination of computation - sequence plus the action, under the constraint that the action must be selected by the computation is also rationality.

Perfect rationality constraints an agent's actions to provide the maximum expectations of success given the information available.

Q.8 What are the functionalities of the agent function?

Ans.: Agent function is a mathematical function which maps each and every possible percept sequence to a possible action.

The major functionality of the agent function is to generate the possible action to each and every percept. It helps the agent to get the list of possible actions the agent can take. Agent function can be represented in the tabular form.

Q.9 Define basic agent program.

Ans.: The basic agent program is a concrete implementation of the agent function which runs on the agent architecture. Agent program puts bound on the length of percent sequence and considers only required percept sequences. Agent program implements the functions of percept sequence and action which are external characteristics of the agent.

Agent program takes input as the current percept from the sensor and return an action to the effectors (Actuators).

Q.10 What are the four components to define a problem? Define them.  AU: May-13

Ans.: The four components to define a problem are,

1. Initial state - It is the state in which agent starts in.

2. A description of possible actions - It is the description of possible actions which are available to the agent.

3. The goal test - It is the test that determines whether a given state is goal (final) state.

4. A path cost function - It is the function that assigns a numeric cost (value) to each path. The problem-solving agent is expected to choose a cost-function that reflects its own performance measure.