Wedge (mechanical device): Difference between revisions

From formulasearchengine
Jump to navigation Jump to search
g
 
en>Postdlf
mNo edit summary
Line 1: Line 1:
You would are aware that there are thousands of solutions for sale on the web when you haven’t been dwelling underneath a rock and roll. You will find lots of electronic books that were surfacing - giving many stuff like losing weight guides, how to herb a tree, getting rid of acne breakouts, teeth bleaching, of course, dating tutorials.<br><br>
{{dablink|This article is about automated planning in artificial intelligence. The term ''strips'' is also used in relation to [[Treasury security]]}}


There are several going out with guides in existence that give fake hopes to the magic of making up review ([http://www.themagicofmakingupsecret.info/ themagicofmakingupsecret.Info]) possibilities individuals. Many of these courting manuals even go when it comes to saying that they promise you a completely success rate. I and You each know that’s utter B.S, proper?<br><br>Avoid thepressure and cash, and time - decide on a thing which can help you with the present challenge. A training course that is aware of just what you are going through…<br><br>5 thoughts - The Magic of Making Up<br><br>What’s Within the Publication?<br><br>The Magic of Making Up is surely an 8 Section e-book that helps you keep your fallen relationship. To acheive your boyfriend or girlfriend again, it provides you with the wisdom and much essential strategies. Seems straightforward huh? Properly, the novel is so thorough and it will help you get more than just each day of studying it to completely grasp its written content.<br><br>It tackles topics that answer what journeyed improper along with your romantic relationship and the way to however get rid of it.<br><br>These will be the 8 Chapters of the Book:<br><br>Section 1: Comprehending Why Your Romance Finished (And Why It is Not Above At This Time)<br><br>Chapter 2: Do not Freak out - Your Factor to Winning Again Their Adore (Taking Your Directly Instantly)<br><br>Section 3: Taking out the Splinter with your Romance (In which Will You Remain? )<br><br>Section 4: Re-igniting the Kindle of Enthusiasm and Wish (The Master Plan)<br><br>Chapter 5: Schedules and Addicts - How Many People May Actually Bring You Backside Along With Your Ex<br><br>Chapter 6: Alleviating Back In Your Partnership to Firm up Your Like<br><br>Chapter 7: Retaining the Enjoy and Enjoyment Without the need of Dredging Up Outdated Cuts and Misunderstandings<br><br>Chapter 8: As Soon As Your Association Can not Be Preserved - Moving Forward with Elegance<br><br>As we discussed - these chapter titles actually provides you with a solid idea of what to look for within this reserve. It is put into pieces making the task of getting your boyfriend or girlfriend rear considerably easier. Make no slip-up concerning this nevertheless - this e-book will not be for those faint hearted. If you would like see great results, while the article author has brilliantly partioned the core elements of the publication, you might still must be completely specialized and kept in.<br><br>The Magic of Making Up provides you with a game prepare you could deal with. As opposed to simply being misplaced and discouraged, being unsure of what to do to win your ex back - you may be supplied an entire tutorial on just what to do to correct your relationship. You will understand more gems and find out more stuff, not alone regarding romantic relationship, as well as about you, when you read each and every section of the guide.<br><br>Learning how to like your own self and increasing by yourself will bring you to even more opportunities. The same as what Chapter 8 states: When your association cannot be kept, you have to move on with sophistication.<br><br>Now, just before getting discouraged, The Magic of Making Up is definitely an efficient guide that may perform the job. Section 8 was created should items definitely can not workout any more in between your therefore you ex. In case your ex in some way got hitched presently, or determined to turn into a nun - The Magic of Making Up will not be capable of do anything to solve that. In such instances, you will need to anticipate to move forward. The novel will lead you for the reason that course of action likewise.<br><br>But furthermore, this reserve is Funds.<br><br>The Magic of Making Up - Right to the stage<br><br>This e book can finest be described in some words: Directly to the stage.<br><br>Who wishes to pay up for one thing that is full of fluff? No-one! This is why the Magic of Making Up is centered on being instantly to the point. The article author realizes your expections - they know why you got it, and that is why he provides on his promise beginning from Web site 1.<br><br>Every single page with this guide can aid you with your quest. Getting the ex back is actually a demanding task, notably if you fellas wound up awful. But panic not for the reason that Magic of Making  magic of making up review ([http://www.themagicofmakingupsecret.info/ themagicofmakingupsecret.Info]) Up will stay true to its title: Magic.<br><br>More about the publication?<br><br>That is really unjust to your creator of your Magic of Making Up, nearly as much as I would like to lower much more gemstones on this content. T.W. Jackson (the article author), designed this publication to help individuals out, having said that, he can’t seriously give all of this understanding apart free of charge. There is good reason why this product is perfect for purchase, and lots of people are buying it.<br><br>To always be reasonable with him, as well as to the a large number of other people who have bought it, why not shell out a few of your cash for that Magic of Making Up. All things considered, it’s very reasonably priced and worth the cost.<br><br>Just where in addition could you obtain an e book that is definitely personalize-intended for getting your ex rear? This publication is definitely up for your challenge, even though that is a quite challenging thing to do.<br><br>Secret of having Up is effective - in the event you work<br><br>If you are prepared to embrace the [http://Www.dailymail.Co.uk/home/search.html?sel=site&searchPhrase=publication publication] and use that which you learn from it - positive things will happen. In case you anticipate to see it and do nothing at all following that, then you’re just setting on your own up to fail.<br><br>The Magic of Making Up is often a amazing arrange that will genuinely assist you to earn your ex again. But the problem is, you can not expect to have it to undertake everything on your behalf. In fact, it is merely a reserve. You are the human staying withforearms and thighs and legs, a brain, in addition to a heart and soul for it to be all occur. In the event you genuinely have faith in the system along with oneself, you could Get YOUR EX Back again.<br><br>Crazier everything has happened on earth, so that you must not lose hope. Once you discover how to acheive it, your boyfriend or girlfriend will love you once again. That is precisely what the Magic of Making Up is for when you never -.
{{TOCright}}
 
In [[artificial intelligence]], '''STRIPS''' ('''St'''anford '''R'''esearch '''I'''nstitute '''P'''roblem '''S'''olver) is an [[automated planning|automated planner]] developed by [[Richard Fikes]] and [[Nils Nilsson (researcher)|Nils Nilsson]] in 1971 at [[SRI International]]. The same name was later used to refer to the [[formal language]] of the inputs to this planner. This language is the base for most of the languages for expressing [[automated planning]] problem instances in use today; such languages are commonly known as [[action language]]s. This article only describes the language, not the planner.
 
==Definition==
 
A STRIPS instance is composed of:
 
* An initial state;
* The specification of the goal states – situations which the planner is trying to reach;
* A set of actions. For each action, the following are included:
** preconditions (what must be established before the action is performed);
** postconditions (what is established after the action is performed).
 
Mathematically, a STRIPS instance is a  quadruple <math>\langle P,O,I,G \rangle</math>, in which each component has the following meaning:
 
# <math>P</math> is a set of ''conditions'' (i.e., [[propositional variable]]s);
# <math>O</math> is a set of ''operators'' (i.e., actions); each operator is itself a quadruple <math>\langle \alpha, \beta, \gamma, \delta \rangle</math>, each element being a set of conditions. These four sets specify, in order, which conditions must be true for the action to be executable, which ones must be false, which ones are made true by the action and which ones are made false;
# <math>I</math> is the initial state, given as the set of conditions that are initially true (all others are assumed false);
# <math>G</math> is the specification of the goal state; this is given as a pair <math>\langle N,M \rangle</math>, which specify which conditions are true and false, respectively, in order for a state to be considered a goal state.
 
A plan for such a planning instance is a sequence of operators that can be executed from the initial state and that leads to a goal state.
 
Formally, a state is a set of conditions: a state is represented by the set of conditions that are true in it. Transitions between states are modeled by a transition function, which is a function mapping states into new states that result from the execution of actions. Since states are represented by sets of conditions, the transition function relative to the STRIPS instance <math>\langle P,O,I,G \rangle</math> is a function
 
: <math>\operatorname{succ}: 2^P \times O \rightarrow 2^P,</math>
 
where <math>2^P</math> is the set of all subsets of <math>P</math>, and is therefore the set of all possible states.
The transition function <math>\operatorname{succ}</math> for a state <math>C \subseteq P</math>, can be defined as follows, using the simplifying assumption that actions can always be executed but have no effect if their preconditions are not met:
 
{|
|-
| <math>\operatorname{succ}(C,\langle \alpha,\beta,\gamma,\delta \rangle)</math>
| = <math>C \backslash \delta \cup \gamma</math> &nbsp; &nbsp; &nbsp; &nbsp;
| if <math>\alpha \subseteq C</math> and <math>\beta \cap C = \varnothing</math>
|-
| &nbsp;
| = <math>C</math>
| otherwise
|}
 
The function <math>\operatorname{succ}</math> can be extended to sequences of actions by the following recursive equations:
 
:<math>\operatorname{succ}(C,[\ ]) = C</math>
:<math>\operatorname{succ}(C,[a_1,a_2,\ldots,a_n])=\operatorname{succ}(\operatorname{succ}(C,a_1),[a_2,\ldots,a_n])</math>
 
A plan for a STRIPS instance is a sequence of actions such that the state that results from executing the actions in order from the initial state satisfies the goal conditions. Formally, <math>[a_1,a_2,\ldots,a_n]</math> is a plan for <math>G = \langle N,M \rangle</math> if <math>F=\operatorname{succ}(I,[a_1,a_2,\ldots,a_n])</math> satisfies the following two conditions:
 
:<math>N \subseteq F</math>
:<math>M \cap F = \varnothing</math>
 
==Extensions==
 
The above language is actually the propositional version of STRIPS; in practice, conditions are often about objects: for example, that the position of a robot can be modeled by a [[Predicate (mathematics)|predicate]] <math>At</math>, and <math>At(room1)</math> means that the robot is in Room1. In this case, actions can have [[free variable]]s, which are implicitly existentially quantified. In other words, an action represents all possible propositional actions that can be obtained by replacing each free variable with a value.
The initial state is considered fully known in the language described above: conditions that are not in <math>I</math> are all assumed false. This is often a limiting assumption, as there are natural examples of planning problems in which the initial state is not fully known. Extensions of STRIPS have been developed to deal with partially known initial states.
 
==A sample STRIPS problem==
 
A monkey is at location A in a lab. There is a box in location C. The monkey wants the bananas that are hanging from the ceiling in location B, but it needs to move the box and climb onto it in order to reach them.
 
Initial state: At(A), Level(low), BoxAt(C), BananasAt(B)
Goal state:    Have(Bananas)
 
Actions:
                // move from X to Y
                _Move(X, Y)_
                Preconditions:  At(X), Level(low)
                Postconditions: not At(X), At(Y)
               
                // climb up on the box
                _ClimbUp(Location)_
                Preconditions:  At(Location), BoxAt(Location), Level(low)
                Postconditions: Level(high), not Level(low)
               
                // climb down from the box
                _ClimbDown(Location)_
                Preconditions:  At(Location), BoxAt(Location), Level(high)
                Postconditions: Level(low), not Level(high)
               
                // move monkey and box from X to Y
                _MoveBox(X, Y)_
                Preconditions:  At(X), BoxAt(X), Level(low)
                Postconditions: BoxAt(Y), not BoxAt(X), At(Y), not At(X)
               
                // take the bananas
                _TakeBananas(Location)_
                Preconditions:  At(Location), BananasAt(Location), Level(high)
                Postconditions: Have(bananas)
 
==Complexity==
 
Deciding the existence of a plan for a propositional STRIPS instance is [[PSPACE|PSPACE-complete]]. Various restrictions can be enforced on the instances to make the problem [[NP-complete]]<ref>Bylander, T. The computational complexity of propositional STRIPS planning Artificial Intelligence, 1994, 69, 165-204.</ref>
 
==See also==
 
* [[Automated planning]]
* [[Hierarchical task network]]
* [[Planning Domain Definition Language]] (PDDL)
* [[Action description language]] (ADL)
* [[Sussman Anomaly]]
 
==Notes==
{{Reflist}}
 
==References==
* C. Bäckström and B. Nebel (1995). Complexity results for SAS+ planning. ''Computational Intelligence'', 11:625-656.
* T. Bylander (1991). Complexity results for planning. In ''Proceedings of the Twelfth International Joint Conference on Artificial Intelligence (IJCAI'91)'', pages 274-279.
* R. Fikes and N. Nilsson (1971). STRIPS: a new approach to the application of theorem proving to problem solving. ''Artificial Intelligence'', 2:189-208.
* {{Russell Norvig 2003}}
 
{{DEFAULTSORT:Strips}}
[[Category:History of artificial intelligence]]
[[Category:Automated planning and scheduling]]
[[Category:SRI International software]]

Revision as of 16:15, 11 January 2014

Template:Dablink

Template:TOCright

In artificial intelligence, STRIPS (Stanford Research Institute Problem Solver) is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. The same name was later used to refer to the formal language of the inputs to this planner. This language is the base for most of the languages for expressing automated planning problem instances in use today; such languages are commonly known as action languages. This article only describes the language, not the planner.

Definition

A STRIPS instance is composed of:

  • An initial state;
  • The specification of the goal states – situations which the planner is trying to reach;
  • A set of actions. For each action, the following are included:
    • preconditions (what must be established before the action is performed);
    • postconditions (what is established after the action is performed).

Mathematically, a STRIPS instance is a quadruple P,O,I,G, in which each component has the following meaning:

  1. P is a set of conditions (i.e., propositional variables);
  2. O is a set of operators (i.e., actions); each operator is itself a quadruple α,β,γ,δ, each element being a set of conditions. These four sets specify, in order, which conditions must be true for the action to be executable, which ones must be false, which ones are made true by the action and which ones are made false;
  3. I is the initial state, given as the set of conditions that are initially true (all others are assumed false);
  4. G is the specification of the goal state; this is given as a pair N,M, which specify which conditions are true and false, respectively, in order for a state to be considered a goal state.

A plan for such a planning instance is a sequence of operators that can be executed from the initial state and that leads to a goal state.

Formally, a state is a set of conditions: a state is represented by the set of conditions that are true in it. Transitions between states are modeled by a transition function, which is a function mapping states into new states that result from the execution of actions. Since states are represented by sets of conditions, the transition function relative to the STRIPS instance P,O,I,G is a function

:2P×O2P,

where 2P is the set of all subsets of P, and is therefore the set of all possible states.

The transition function for a state CP, can be defined as follows, using the simplifying assumption that actions can always be executed but have no effect if their preconditions are not met:

(C,α,β,γ,δ) = Cδγ         if αC and βC=
  = C otherwise

The function can be extended to sequences of actions by the following recursive equations:

(C,[])=C
(C,[a1,a2,,an])=((C,a1),[a2,,an])

A plan for a STRIPS instance is a sequence of actions such that the state that results from executing the actions in order from the initial state satisfies the goal conditions. Formally, [a1,a2,,an] is a plan for G=N,M if F=(I,[a1,a2,,an]) satisfies the following two conditions:

NF
MF=

Extensions

The above language is actually the propositional version of STRIPS; in practice, conditions are often about objects: for example, that the position of a robot can be modeled by a predicate At, and At(room1) means that the robot is in Room1. In this case, actions can have free variables, which are implicitly existentially quantified. In other words, an action represents all possible propositional actions that can be obtained by replacing each free variable with a value.

The initial state is considered fully known in the language described above: conditions that are not in I are all assumed false. This is often a limiting assumption, as there are natural examples of planning problems in which the initial state is not fully known. Extensions of STRIPS have been developed to deal with partially known initial states.

A sample STRIPS problem

A monkey is at location A in a lab. There is a box in location C. The monkey wants the bananas that are hanging from the ceiling in location B, but it needs to move the box and climb onto it in order to reach them.

Initial state: At(A), Level(low), BoxAt(C), BananasAt(B)
Goal state:    Have(Bananas)
Actions:
               // move from X to Y
               _Move(X, Y)_
               Preconditions:  At(X), Level(low)
               Postconditions: not At(X), At(Y)
               
               // climb up on the box
               _ClimbUp(Location)_
               Preconditions:  At(Location), BoxAt(Location), Level(low)
               Postconditions: Level(high), not Level(low)
               
               // climb down from the box
               _ClimbDown(Location)_
               Preconditions:  At(Location), BoxAt(Location), Level(high)
               Postconditions: Level(low), not Level(high)
               
               // move monkey and box from X to Y
               _MoveBox(X, Y)_
               Preconditions:  At(X), BoxAt(X), Level(low)
               Postconditions: BoxAt(Y), not BoxAt(X), At(Y), not At(X)
               
               // take the bananas
               _TakeBananas(Location)_
               Preconditions:  At(Location), BananasAt(Location), Level(high)
               Postconditions: Have(bananas)

Complexity

Deciding the existence of a plan for a propositional STRIPS instance is PSPACE-complete. Various restrictions can be enforced on the instances to make the problem NP-complete[1]

See also

Notes

43 year old Petroleum Engineer Harry from Deep River, usually spends time with hobbies and interests like renting movies, property developers in singapore new condominium and vehicle racing. Constantly enjoys going to destinations like Camino Real de Tierra Adentro.

References

  • C. Bäckström and B. Nebel (1995). Complexity results for SAS+ planning. Computational Intelligence, 11:625-656.
  • T. Bylander (1991). Complexity results for planning. In Proceedings of the Twelfth International Joint Conference on Artificial Intelligence (IJCAI'91), pages 274-279.
  • R. Fikes and N. Nilsson (1971). STRIPS: a new approach to the application of theorem proving to problem solving. Artificial Intelligence, 2:189-208.
  • Template:Russell Norvig 2003
  1. Bylander, T. The computational complexity of propositional STRIPS planning Artificial Intelligence, 1994, 69, 165-204.