AR facts Flashcards
What is the purpose of the controller of an agent?
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.
Jitter
A deviation from true periodicity of a presumably periodic signal
3 examples of probability distribution
Binomial distribution, Uniform distribution, Poisson distribution
2 event arrival patterns and example
Periodic arrival pattern: jitter
Aperiodic arrival pattern: bounded, unbounded, bursty, irregular
Actions
Reactions to events
5 Inputs an agent uses for its computations
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
State
A State models a situation in time during which some invariant
condition holds.
Real-time system
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.
Laxity
Specifies the type of deadline, hard or soft.
Transition system
A transition system consists of states & directed transitions
Event
An event is a something that may occur at a specific instant in time.
Examples: (state) change event, time event, message event
What is linear regression?
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.
Difference between normal and Gaussian distribution?
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”.
Priority
The priority of the action from a scheduling perspective. It may a result of static analysis or by dynamic scheduling software.
Blocking time
The length of time that the action is blocked waiting for resources.
Is atomic
Identifies whether the action can be pre-empted or not.
Absolute deadline
Specifies the final instant by which the action must be complete. This may be either a hard or a soft deadline.
Relative deadline
For soft deadlines, specifies the desired time by which the action should be complete.
Blocking time
The length of time that the action is blocked waiting for resources.
Ready time
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.
Delay time
The length of time an action that is eligible for execution waits while acquiring and releasing resources.
Release time
The instant of time at which a scheduling job becomes eligible for execution.
Preempted time
The length of time the action is preempted, when runable, to make way for a higher-priority action.
Worst-case Completion time
The overall time taken to execute the action, including overheads.
Duration
The total duration of the action (not used if start and end times are defined).
Bounded
Between a minimum interarrival time and maximum interarrival time.
Unbounded
No minimun interarrival time and maximum interarrival time.
Stochastic according to a probability distribution
Bursty
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
Irregular
Nothing to see, move on
Labeled transition system
A transition system consists of states & directed transitions and labels 1 for every transition
Finite state machines
- 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
State transition table
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)
UML state machine
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
Why does one, in most cases, has to translate the data from the sensors into information suitable for the controller?
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)
