AR facts

Question 1

What is the purpose of the controller of an agent?

Answer 1

The controller of an agent (software) receives and interpreters the precepts received from the sensor in the body. It sends commands to the Actuator of the robot on how the state of the world should be changed.

Question 2

Jitter

Answer 2

A deviation from true periodicity of a presumably periodic signal

Question 3

3 examples of probability distribution

Answer 3

Binomial distribution, Uniform distribution, Poisson distribution

Question 4

2 event arrival patterns and example

Answer 4

Periodic arrival pattern: jitter
Aperiodic arrival pattern: bounded, unbounded, bursty, irregular

Question 5

Actions

Answer 5

Reactions to events

Question 6

5 Inputs an agent uses for its computations

Answer 6

Abilities : set of possible actions it can perform
Goals/Preferences : it wants, its desires, its values,…
Prior Knowledge : built-in knowledge
History : interaction with the environment
* Stimuli : it receives from environment now (observations, percepts)
* Past experiences : it has received in the past

Question 7

State

Answer 7

A State models a situation in time during which some invariant
condition holds.

Question 8

Real-time system

Answer 8

Type of deadline
Hard: Missing a deadline is a total system failure.
Firm: Infrequent deadline misses are tolerable, but may degrade the system’s quality of service. The usefullness of a result is zero after its deadline.
Soft: The usefulness of a result degrades after its deadline, thereby degrading the system’s quality of service.

Question 9

Laxity

Answer 9

Specifies the type of deadline, hard or soft.

Question 10

Transition system

Answer 10

A transition system consists of states & directed transitions

Question 11

Event

Answer 11

An event is a something that may occur at a specific instant in time.
Examples: (state) change event, time event, message event

Question 12

What is linear regression?

Answer 12

In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable’s value is called the independent variable.

Question 13

Difference between normal and Gaussian distribution?

Answer 13

Normal distribution, also known as the Gaussian distribution, is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean.
In graphical form, the normal distribution appears as a “bell curve”.

Question 14

Priority

Answer 14

The priority of the action from a scheduling perspective. It may a result of static analysis or by dynamic scheduling software.

Question 15

Blocking time

Answer 15

The length of time that the action is blocked waiting for resources.

Question 16

Is atomic

Answer 16

Identifies whether the action can be pre-empted or not.

Question 17

Absolute deadline

Answer 17

Specifies the final instant by which the action must be complete. This may be either a hard or a soft deadline.

Question 18

Relative deadline

Answer 18

For soft deadlines, specifies the desired time by which the action should be complete.

Question 19

Blocking time

Answer 19

The length of time that the action is blocked waiting for resources.

Question 20

Ready time

Answer 20

The effective Release Time expressed as the length of time since the beginning of a period; delay between the time an entity is eligible for execution and the actual beginning.

Question 21

Delay time

Answer 21

The length of time an action that is eligible for execution waits while acquiring and releasing resources.

Question 22

Release time

Answer 22

The instant of time at which a scheduling job becomes eligible for execution.

Question 23

Preempted time

Answer 23

The length of time the action is preempted, when runable, to make way for a higher-priority action.

Question 24

Worst-case Completion time

Answer 24

The overall time taken to execute the action, including overheads.

Question 25

Duration

Answer 25

The total duration of the action (not used if start and end times are defined).

Question 26

Bounded

Answer 26

Between a minimum interarrival time and maximum interarrival time.

Question 27

Unbounded

Answer 27

No minimun interarrival time and maximum interarrival time. Stochastic according to a probability distribution

Question 28

Bursty

Answer 28

Positive correlation in the between arrival of one message and the near arrival of the next. * Maximum burstlength * Burst interval * stochastic according to a probability distribution

Question 29

Irregular

Answer 29

Nothing to see, move on

Question 30

Labeled transition system

Answer 30

A transition system consists of states & directed transitions and labels 1 for every transition

Question 31

Finite state machines

Answer 31

* have a set of states and transitions, * have at least one state, * cannot have an infinite number of states, * have one starting state, which is the first state that is activated upon their execution, * may or may not have accepting (= final) states, * have for each transition a set of symbols (labels), * have an alphabet which is the union of all the sets of transition symbols (path of labels) * can have an infinite alphabet

Question 32

State transition table

Answer 32

A state-transition table is a table showing what to state a finite-state machine will move to, based on the current state and other inputs. * 1 dimensional table: list of states, labels, next state (, output), * 2 dimensional table: * list of states, list of labels, next states (, output), * list of states, list of states, boolean (reachability) * list of states, list of states, probability (Markov chain)

Question 33

UML state machine

Answer 33

Object oriented variant of Harel statecharts, combination of Mealy machines (current state based transitions) and Moore machines (input based transitions): * actions: * entry: when entering a state * during: while in the state * exit: when exiting the state * transition: during the transition * hierarchical/embedded state

Question 34

Why does one, in most cases, has to translate the data from the sensors into information suitable for the controller?

Answer 34

In most cases the data from the sensors has to be translated because the sensor data obtained from the environment is continuous and needs to be translated to a discrete format that the controller software can work with (A computer can only calculate with integers)