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Nalazenje optimalnih strategija pretrage u grafovima podrazumeva:
- Pronalazenje puta najvece tezine
- Pronalazenje puta najmanje duzine
- Pronalazenje puta najmanje tezine
- Pronalazenje puta najvece duzine

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2.

Strategija se karakterisu preko sledecih pokazatelja:
- Sirina
- Kompleksnost
- Optimalnost
- Dubina
- Heuristika
- Vremenska kompleksnost
- Prostorna kompleksnost
Correct Answer(s)

A. Kompleksnost
A. Optimalnost
A. Vremenska kompleksnost
A. Prostorna kompleksnost

Explanation

The given answer includes the factors that characterize a strategy. These factors are complexity, optimality, time complexity, and space complexity. Complexity refers to the level of difficulty or intricacy of the strategy. Optimality means that the strategy is the best or most efficient solution for the given problem. Time complexity refers to the amount of time required for the strategy to execute. Space complexity refers to the amount of memory or storage space needed for the strategy. Therefore, the answer includes the important indicators that define a strategy.

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3.

Vremenska kompleksnost algoritma se moze izraziti:
- Ukupnim brojem generisanih (otvorenih) cvorova
- Ukupnim brojem cvorova koji nemaju naslednike
- Brojem corova u listi OPEN
Correct Answer

A. Ukupnim brojem generisanih (otvorenih) cvorova

Explanation

The correct answer is "Ukupnim brojem generisanih (otvorenih) cvorova". This means that the time complexity of the algorithm can be expressed by the total number of generated (open) nodes. This suggests that the algorithm's efficiency or performance can be measured by the number of nodes it generates during its execution.

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4.

U grafu tipa stablo, koren je cvor koji:
- Ima samo jednog roditelja
- Ima vise od jednog roditelja
- Nema roditelja
Correct Answer

A. Nema roditelja

Explanation

In a tree graph, the root node does not have any parent nodes. It is the topmost node in the hierarchy and serves as the starting point for traversing the tree. Since there are no nodes above it, it does not have any parents.

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5.

Ako je usmerenost pretrage P=1, tada vazi:
- Algoritam otvara veliki broj nepotrebnih cvorova
- Algoritam otvara mali broj nepotrebnih cvorova
- Algoritam nalazi direktno resenje do cilja
Correct Answer

A. Algoritam nalazi direktno resenje do cilja

Explanation

If the search direction is P=1, it means that the algorithm is using a heuristic function that provides direct guidance towards the goal state. Therefore, the algorithm is able to find the solution directly without exploring unnecessary nodes.

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6.

Kod A* algoritma pretrage, u funkciji "f(n)= g(n) + h(n)", f(n) je: ***
- Akumulirana cena parcijalne putanje
- Heuristicki procena cene preostale putanje do ciljnog cvora
- Procena cene putanje do cilja pod uslovom da prolazi kroz cvor n
Correct Answer

A. Procena cene putanje do cilja pod uslovom da prolazi kroz cvor n

Explanation

In the A* search algorithm, the function "f(n) = g(n) + h(n)" represents the estimated cost of the path from the start node to the goal node, passing through node n. The function takes into account two factors: g(n) represents the accumulated cost of the partial path from the start node to node n, while h(n) represents the heuristic estimate of the remaining cost from node n to the goal node. By summing these two values, the algorithm can prioritize nodes that have a lower estimated cost, leading to more efficient search and finding the optimal path.

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7.

Ukoliko za rešavanje datog problema posedujemo dodatne informacije vezane za prirodu rešavanog problema, a koje nam olakšavaju odluku o tome koji naredni čvor treba otkriti u grafu pretrage, u pitanju je:
- Pretraga u sirinu
- Heuristicka pretraga
- Pretraga sa iterativnim produbljivanjem
Correct Answer

A. Heuristicka pretraga

Explanation

The correct answer is "Heuristicka pretraga" because it states that if we have additional information about the nature of the problem being solved, which helps us decide which next node to discover in the search graph, then it is heuristic search.

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8.

Kod A* algoritma pretrage, u funkciji "f(n) = g(n) + h(n)", h(n) je:
- Procena cene putanje koja prosiruje trenutnu putanju
- Heuristicki procena cene preostale putanje od cvora n do ciljnog cvora
- Akumulirana cena parcijalne putanje
Correct Answer

A. Heuristicki procena cene preostale putanje od cvora n do ciljnog cvora

Explanation

In the A* search algorithm, the function "f(n) = g(n) + h(n)" is used to estimate the cost of a path. In this context, "h(n)" refers to the heuristic estimation of the remaining cost of the path from node "n" to the goal node. This heuristic estimation helps guide the algorithm towards the goal by considering the potential cost of the remaining path. It is a crucial component in determining the priority of nodes to be explored and ultimately finding the optimal path in the search process.

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9.

Specificne informacije vezane za datu problemsku oblast koje olakšavaju procenu perspektivnosti mogućih alternativnih akcija u toku rešavanja datog problema, zovu se:
- Problemske informacije
- Alternativne informacije
- Heuristicke informacije
Correct Answer

A. Heuristicke informacije

Explanation

Heuristicke informacije su specificne informacije vezane za datu problemsku oblast koje olakšavaju procenu perspektivnosti mogućih alternativnih akcija u toku rešavanja datog problema. Heuristike su pravila ili smernice koje se koriste kao mentalni skraćenice za donošenje brzih odluka ili rešavanje problema. One pružaju korisne smernice ili pretpostavke koje mogu pomoći u donošenju odluka kada nema dovoljno vremena ili resursa za detaljnu analizu. U ovom kontekstu, heuristicke informacije bi mogle biti korisne za procenu perspektivnosti alternativnih akcija u rešavanju problema.

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10.

Graf se sastoji od:
- Grafika
- Cvorova
- Grana
- Algoritama
Correct Answer(s)

A. Cvorova
A. Grana

Explanation

A graph consists of nodes (also known as vertices) and edges (also known as edges). Nodes represent the entities or objects in the graph, while edges represent the connections or relationships between the nodes. Therefore, the correct answer is "Nodes, Edges."

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11.

Strategije pretrage definisu:
- Redosled otvaranja cvorova pretrage
- Brzinu otvaranja cvorova pretrage
- Najvecu dozvoljenu dubinu pri otvaranju cvorova pretrage
Correct Answer

A. Redosled otvaranja cvorova pretrage

Explanation

Strategije pretrage definisu redosled otvaranja cvorova pretrage. To znači da strategije pretrage određuju u kojem redosledu će se otvarati cvorovi tokom pretrage, što može imati značajan uticaj na efikasnost pretrage. Na primer, strategija pretrage u širinu će otvarati sve cvorove na jednom nivou pre nego što pređe na sledeći nivo, dok će strategija pretrage u dubinu otvarati cvorove sve do najveće dozvoljene dubine pre nego što se vrati na prethodni cvor. Dakle, redosled otvaranja cvorova pretrage je ono što strategije pretrage definišu.

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12.

Prostorna kompleksnost se moze izraziti preko:
- Ukupnog broja cvorova u listi OPEN
- Ukupnog broja memorisanih cvorova
- Ukupnog broja cvorova u listi CLOSED
- Ukupnog broja generisanih (otvorenih) cvorova
Correct Answer

A. Ukupnog broja memorisanih cvorova

Explanation

The correct answer is "Ukupnog broja memorisanih cvorova" because the spatial complexity of a problem can be measured by the total number of nodes stored in memory during the execution of an algorithm. This includes both the nodes in the OPEN list (nodes that have been generated but not yet expanded) and the nodes in the CLOSED list (nodes that have been expanded and their successors have been generated). The total number of generated nodes may be larger than the number of nodes stored in memory at any given time, as some nodes may have been expanded and removed from memory.

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13.

Ako su dve moguce heuristicke funkcije u A* algoritmu u odnosu h1(n) > h2(n), tacan je sledeci iskaz:
- H2 otvara vise cvorova od h1
- H1 otvara vise cvorova od h2
- H1 i h2 otvaraju isti broj cvorova
- Broj otvorenih cvorova moze biti u bilo kom odnosu
Correct Answer

A. H2 otvara vise cvorova od h1

Explanation

The correct answer is H2 otvara vise cvorova od h1. This means that the heuristic function H2 expands more nodes than H1 in the A* algorithm.

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14.

U grafu tipa stablo, dubina cvora tipa koren je:
- 0
- 1
- Beskonacna
Correct Answer

A. 0

Explanation

In a tree graph, the depth of a node refers to the number of edges in the longest path from the root node to that particular node. Since the root node is the highest node in the tree, it does not have any edges leading to it. Therefore, the depth of the root node is 0.

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15.

Ako je tacna vrednost za h(n)=5, za neki čvor u grafu pretrage, da li je u A* algoritmu moguće da procena h(n) za taj čvor bude h(n)=6:
- Da
- Ne
- Nije bitno
Correct Answer

A. Da

Explanation

In A* algorithm, h(n) represents the heuristic function which estimates the cost from the current node to the goal node. The algorithm combines the actual cost from the start node to the current node (g(n)) and the heuristic cost from the current node to the goal node (h(n)) to make decisions on which path to explore. Therefore, it is possible for the estimate h(n) to be 6 if the heuristic function overestimates the actual cost.

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16.

Ako je heuristička funkcija u A* algoritmu oblika h(n)=C * (1/d(n)), gde je C konstanta, a d(n) dubina čvorova u grafu pretrage, u početku rada će algoritam imati svojstvo:
- Pretrage u sirinu
- Usmerene pretrage
- Nije bitno
- Pretrage u dubinu
Correct Answer

A. Pretrage u sirinu

Explanation

The given heuristic function h(n) = C * (1/d(n)) in the A* algorithm is inversely proportional to the depth of the nodes in the search graph. This means that nodes with smaller depths will have larger heuristic values, while nodes with larger depths will have smaller heuristic values. In the beginning of the algorithm, when all nodes are at the same depth, the heuristic values will be equal for all nodes. This property aligns with the breadth-first search strategy, where nodes at the same depth are explored before moving to nodes at deeper depths. Therefore, the algorithm will exhibit the property of breadth-first search in the beginning.

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17.

Grane grafa mogu biti:
- Reverzne
- Neusmerene
- Usmerene
- Inverzne
Correct Answer(s)

A. Neusmerene
A. Usmerene

Explanation

The correct answer is "Neusmerene, Usmerene" because these are the possible types of edges in a graph. "Neusmerene" refers to undirected edges, where there is no specific direction associated with the relationship between two vertices. "Usmerene" refers to directed edges, where there is a specific direction associated with the relationship between two vertices.

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18.

Ako u A* algoritmu h(n) zadovoljava uslov monotonosti, da li se može desiti promena ukazatelja u toku izvršenja programa GRApHSEARCH:
- Da
- Ne
- Nije bitno
Correct Answer

A. Ne

Explanation

In the A* algorithm, the heuristic function h(n) represents the estimated cost from node n to the goal node. If h(n) satisfies the condition of monotonicity, it means that the estimated cost from any node n to the goal node is always less than or equal to the actual cost from n to the goal node. Therefore, there is no need to change the pointer during the execution of the GRAPHSEARCH program as the estimated cost will always be consistent and reliable.

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19.

U grafovima, dohvatljivim se smatraju cvorovi do kojih:
- Vodi jedan, i samo jedan put
- Ne vodi nijedan put
- Vodi jedan ili vise puteva
- Vodi vise od jednog puta
Correct Answer

A. Vodi jedan ili vise puteva

Explanation

In graph theory, reachable nodes are those that can be reached from a given node. The answer "Vodi jedan ili vise puteva" means that a reachable node can be reached by one or more paths. This implies that there can be multiple ways to reach a particular node from the given node, which may involve traversing different edges or vertices in the graph.

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20.

Cvor u grafu moze istovremeno biti i roditelj i dete:
- Tacno
- Netacno
Correct Answer

A. Tacno

Explanation

In a graph, a node can be both a parent and a child at the same time. This is possible in cases where there is a cycle in the graph, meaning that there is a path that starts and ends at the same node. In such cases, the node will have an incoming edge as a child and an outgoing edge as a parent, making it both a parent and a child simultaneously. Therefore, the statement "A node in a graph can be both a parent and a child at the same time" is true.

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21.

Stablo je graf kod koga vazi sledece pravilo:
- Svako dete ima samo jednog roditelja
- Svaki roditelj ima samo jedno dete
- Jedan roditelj moze imati jedno dete, jedno dete moze imati samo jednog roditelja
Correct Answer

A. Svako dete ima samo jednog roditelja

Explanation

The statement suggests that in this graph, each child has only one parent. This means that there is a one-to-one relationship between parents and children.

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22.

U grafu tipa stablo, list je cvor koji:
- Nema dece
- Ima samo jedno dete
- Ima vise od jednog deteta
Correct Answer

A. Nema dece

Explanation

In a tree graph, a leaf node is a node that does not have any children.

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23.

Cena primene pravila u grafovima se moze izraziti:
- Tezinom grana
- Dubinom grana
- Visinom grana
Correct Answer

A. Tezinom grana

Explanation

The correct answer is "Tezinom grana." This means that the application of rules in graphs can be expressed through the weight of the edges. In graph theory, the weight of an edge represents a numerical value that indicates the significance or cost associated with traversing that edge. By assigning weights to the edges, we can quantify the impact or importance of each edge in the graph, allowing us to analyze and make decisions based on these weights.

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24.

Algoritam A* je dopustiv:
- Tacno
- Netacno
Correct Answer

A. Tacno

Explanation

The correct answer is "Tacno" which means "True" in English. This suggests that the A* algorithm is admissible. An admissible algorithm is one that guarantees to find the optimal solution or a solution with a cost that is no greater than the actual optimal cost. Therefore, the A* algorithm is considered valid and reliable in finding optimal solutions in various problem-solving domains.

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25.

Kod A* algoritma pretrage, u funkciji "f(n) = g(n) + h(n)", g(n) je:
- Procena cene putanje koja prosiruje trenutnu putanju
- Procena cene vec predjenog puta od cvora n
- Heuristicki procena cene preostale putanje do ciljnog cvora
Correct Answer

A. Procena cene putanje koja prosiruje trenutnu putanju

Explanation

In the A* search algorithm, the function "f(n) = g(n) + h(n)" is used to estimate the cost of a path. Here, g(n) represents the estimated cost of the path that extends the current path. Therefore, the correct answer is "Procena cene putanje koja prosiruje trenutnu putanju" which translates to "Estimation of the cost of the path that extends the current path."

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26.

Da li je algoritam pretrage u sirinu A* algoritam?
- Da
- Ne
Correct Answer

A. Da

Explanation

The given answer "Da" is correct because the question asks whether the breadth-first search algorithm is the A* algorithm. The A* algorithm is a combination of both the breadth-first search and the best-first search algorithms, so it includes the breadth-first search algorithm as one of its components. Therefore, the answer "Da" is correct.

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27.

Ako u A* algoritmu h(n) zadovoljava uslov monotonosti, da li se moze desiti promena ukazatelja u toku izvrsavanja programa GRApHSEARCH:
- Usmerene pretrage
- Pretrage u sirinu
- Nije bitno
Correct Answer

A. Usmerene pretrage

Explanation

If h(n) satisfies the condition of monotonicity in the A* algorithm, it means that the estimated cost from the current node to the goal node is always less than or equal to the estimated cost from the current node to any successor node plus the estimated cost from that successor node to the goal node. This property ensures that the A* algorithm will always find the optimal solution. Therefore, in the GRAPHSEARCH program, which includes directed searches and breadth-first searches, the change of pointers during execution will not affect the correctness of the algorithm as long as h(n) remains monotonic.

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28.

U neinformativne pretrage spadaju:
- Pretraga u sirinu
- Pretraga u dubinu
- Pretraga uniformnih cena (tezina)
- Heuristicka pretraga
- Stohasticka pretraga
- Semanticka pretraga
Correct Answer(s)

A. Pretraga u sirinu
A. Pretraga u dubinu
A. Pretraga uniformnih cena (tezina)

Explanation

The correct answer includes "Pretraga u sirinu, Pretraga u dubinu, Pretraga uniformnih cena (tezina)". These search methods are all examples of uninformed search algorithms, which means they do not use any additional knowledge or heuristics to guide the search process. They explore the search space systematically without considering the problem-specific information. This is in contrast to heuristic search algorithms, such as Heuristicka pretraga, which use problem-specific knowledge to guide the search process and potentially find solutions more efficiently. Stohasticka pretraga and Semanticka pretraga are not mentioned in the correct answer, so they are not considered as uninformed search methods.

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29.

Kod neinformativne pretrage sa iterativnim produbljivanjem, u stablu sa najvecom dubinom N, ukoliko je incijlano ogranicenje dubine takodje N, ovakva pretraga se moze poistovetiti sa:
- Pretragom u dubinu
- Pretragom u sirinu
- Informisanom pretragom
Correct Answer

A. Pretragom u dubinu

Explanation

The given correct answer suggests that in a non-informative search with iterative deepening, when the maximum depth of the tree is N and the depth limit is also N, this type of search can be equated to Depth-First Search.

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30.

Kod neinformativne pretrage sa iterativnim produbljivanjem, u stablu sa najvecom dubinom N, ukoliko je inicijalno ogranicenje dubine 1, i u svakoj iteraciji se ogranicenje povecava za 1, ovakva pretraga se moze poistovetiti sa:
- Pretragom u dubinu
- Pretragom u sirinu
- Informisanom pretragom
Correct Answer

A. Pretragom u sirinu

Explanation

In the given scenario, the search is performed iteratively with increasing depth limits. This approach is commonly known as iterative deepening depth-first search (IDDFS). In IDDFS, the search starts with a depth limit of 1 and gradually increases the limit by 1 in each iteration. This strategy allows the search to explore the tree in a depth-first manner while still guaranteeing completeness. Therefore, the given scenario can be equated to a breadth-first search, as it explores the tree level by level, similar to how breadth-first search operates.

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31.

Princip SA algoritma se primenjuje u:
- Vestackoj inteligenciji
- Matematici
- Logici
- Metalurgiji
Correct Answer

A. Metalurgiji

Explanation

The principle of algorithm is applied in metalurgy to optimize and streamline various processes such as extraction, purification, and alloying of metals. Algorithms are used to design and control the complex systems involved in metalurgy, ensuring efficient and cost-effective production. By applying algorithms, metalurgists can analyze and predict the behavior of metals under different conditions, leading to advancements in metallurgical techniques and the development of new materials with improved properties.

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32.

Lokalne pretrage po snopu:
- Zapocinje precizno definisanim izborom snopa
- Zapocinje slucajnim izborom k pocetnih stanja
- Zapocinje sluajnim izborom k pocetnih snopova
- Zapocinje precizno definisanim izborom pocetnog stanja
Correct Answer

A. Zapocinje slucajnim izborom k pocetnih stanja
33.

HC algoritam - Uspon sa slucajnim ponovnim kretanjem funkcionise tako sto se:
- Kriterijumom globalnog maksimuma generisu naslednici sve dok se ne generise prvi koji je bolji od tekuceg stanja
- HC procedura startuje vise puta sa razlicitim slucajno izabranim pocetnim stanjima, sve dok se ne dostigne cilj
- HC procedura startuje sa precizno definisanim pocetnim stanjima kojim se dostize prethodno izracunati cilj
Correct Answer

A. HC procedura startuje vise puta sa razlicitim slucajno izabranim pocetnim stanjima, sve dok se ne dostigne cilj

Explanation

The correct answer states that the Hill Climbing (HC) procedure starts multiple times with different randomly selected initial states until the goal is reached. This means that the algorithm does not settle for the first better successor generated, but continues to explore different paths by restarting with different initial states. This approach increases the chances of finding the global maximum and improves the algorithm's effectiveness in reaching the goal.

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34.

HC algoritam - Uspon prvog izbora:
- Kriterijumom globalnog maksimuma generise naslednike sve dok se ne generise prvi koji je bolji od tekuceg stanja
- Na slucajan nacin generise naslednike sve dok se ne generise prvi koji je bolji od tekuceg stanja
- Na slucajan nacin generise prethodnike sve dok se ne generise prvi koji je nizi od tekuceg stanja
Correct Answer

A. Na slucajan nacin generise naslednike sve dok se ne generise prvi koji je bolji od tekuceg stanja

Explanation

The correct answer is "Na slucajan nacin generise naslednike sve dok se ne generise prvi koji je bolji od tekuceg stanja." This is because the algorithm uses a random method to generate successors until it generates the first one that is better than the current state.

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35.

GA predstavlja:
- Ireverzibilni proces
- Iterativni proces
- Reverzibilni proces
- Usmereni proces
Correct Answer

A. Iterativni proces

Explanation

The correct answer is "Iterativni proces" which translates to "Iterative process" in English. An iterative process refers to a process that involves repeating a series of steps or actions multiple times in order to achieve a desired outcome. It is a systematic approach that allows for continuous improvement and refinement through repetition and learning from previous iterations. This type of process is commonly used in various fields such as software development, problem-solving, and decision-making.

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36.

Koje svojstvo ima algoritam koji poseduje osobinu optimalnosti: ***
- U vecini slucajeva dobro resenje
- Uvek nalazi optimalno resenje
- Ponekad nalazi optimlano resenje
Correct Answer

A. Uvek nalazi optimalno resenje

Explanation

An algorithm that possesses the property of optimality always finds the optimal solution. This means that regardless of the input or the specific problem, the algorithm will consistently provide the best possible solution. It does not settle for suboptimal solutions or approximate answers but guarantees the optimal outcome.

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37.

Stohasticki HC algoritam:
- Na slucajan nacin bira korake medju onima koji vode nanize
- Na stohasticki nacin bira pocetna stanja i restartuje proceduru
- Na slucajan nacin bira korake medju onima koji vode navise
- Na slucajan nacin bira pocetna stanja i restartuje proceduru
Correct Answer

A. Na slucajan nacin bira korake medju onima koji vode navise

Explanation

The correct answer is "Na slucajan nacin bira korake medju onima koji vode navise." This means that the Stohasticki HC algorithm randomly selects steps that lead upwards. This suggests that the algorithm is designed to explore higher-value solutions in a random and stochastic manner.

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38.

Efikasne strategije upravljanja zahtevaju dovoljno informacija o prirodi resavanog problema, nazivaju se: ***
- Reverznim
- Nepovratnim
- Heuristickim
Correct Answer

A. Heuristickim

Explanation

Heurističke strategije upravljanja zahtevaju dovoljno informacija o prirodi rešavanog problema. Heuristika se odnosi na korišćenje iskustva i znanja kako bi se donela brza odluka ili pronašlo zadovoljavajuće rešenje, iako nije nužno optimalno. Heuristike su često korisne u situacijama kada je potrebno brzo rešiti problem, a ne postoji dovoljno vremena ili resursa za analizu svih mogućnosti.

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39.

Cilj GA je:
- Generalizacija analize neuronskih mreza u cilju resavanja istrazivackih problema
- Racunarska imitacija procesa na kojima pociva prirodna selekcija
- Generalizacija analize neuronskih mreza u cilju resavanja poslovnih problema
Correct Answer

A. Racunarska imitacija procesa na kojima pociva prirodna selekcija

Explanation

The goal of GA is to simulate computer processes based on natural selection.

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40.

Raspored hladjenja (Cooling Schedule) je:
- Promena pocetnih uslova u SA algoritmu
- Kriterijum zaustavljanja SA algoritma
- Promena parametara temperature kroz iteracije SA algoritma
Correct Answer

A. Promena parametara temperature kroz iteracije SA algoritma

Explanation

The cooling schedule refers to the process of changing the temperature parameters throughout the iterations of the Simulated Annealing (SA) algorithm. This schedule determines how quickly or slowly the temperature decreases during the optimization process. By gradually reducing the temperature, the algorithm explores a larger search space at higher temperatures and focuses on exploiting local optima at lower temperatures. This allows the algorithm to escape local optima and converge towards a global optimum solution.

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41.

Genetski algoritmi koriste tri operatora:
- Definicija, rekombinacija, mutacija
- Definicija, krosover, mutacija
- Selekcija, krosover, mutacija
- Selekcija, rekombinacija, mutacija
Correct Answer(s)

A. Selekcija, krosover, mutacija
A. Selekcija, rekombinacija, mutacija

Explanation

The correct answer is "Selekcija, krosover, mutacija". This is because genetic algorithms typically involve three main operators: selection, crossover, and mutation. Selection involves choosing individuals from a population based on their fitness for reproduction. Crossover involves combining genetic material from two parents to create offspring. Mutation involves introducing random changes in the genetic material to promote diversity and exploration of the search space. The given answer includes all three of these operators, making it the correct choice.

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42.

Ako se temperatura u SA algoritmu suvise sporo menja:
- Konvergencija je brza
- Konvergencija je spora
- Ne utice na konvergenciju
Correct Answer

A. Konvergencija je spora

Explanation

If the temperature in the SA algorithm changes too slowly, it means that the algorithm takes a longer time to converge. This is because the SA algorithm uses temperature as a parameter to control the acceptance of worse solutions in order to explore the search space effectively. If the temperature changes slowly, it implies that the algorithm is not exploring the search space efficiently and is stuck in local optima. Therefore, the convergence of the algorithm is slow.

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43.

Proceduralna znanja su:
- Znanja koja nastaju kao posledica primene procedura VI
- Znanja koja proisticu iz stohastickih procedura VI
- Neodvojiva od procedure koje ih koriste
Correct Answer

A. Neodvojiva od procedure koje ih koriste

Explanation

Proceduralna znanja su neodvojiva od procedure koje ih koriste. This means that procedural knowledge cannot be separated from the procedure that utilizes it. In other words, procedural knowledge is closely tied to the specific process or procedure in which it is applied. It is a type of knowledge that is acquired through the experience of carrying out a particular procedure and is intimately connected to the steps and actions involved in that procedure.

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44.

U SA algoritmu, parametar temperatura je: ***
- Konstantan parametar
- Povecava se sa brojem iteracija rada
- Smanjuje se sa brojem iteracija rada
Correct Answer

A. Smanjuje se sa brojem iteracija rada

Explanation

The parameter temperature in the algorithm decreases with the number of iterations.

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45.

Ako se temperatura u SA algoritmu suvise brzo smanjuje:
- Nije od vaznosti za rad algoritma
- Algoritam moze da promasi globalni ekstrem
- Algoritam ce poceti da osciluje
Correct Answer

A. Algoritam moze da promasi globalni ekstrem

Explanation

If the temperature in the SA algorithm decreases too quickly, it means that the algorithm is cooling down rapidly. This can lead to the algorithm skipping over the global extreme point, which is the optimal solution. The algorithm needs a slower decrease in temperature to explore the search space effectively and converge towards the global extreme.

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46.

Jedna strategija je kompletna ako:
- Uvek nalazi resenje, ako postoji
- Da li ce naci resenje, zavisi od problema do problema
- Ponekad i nadje resenje
- Uvek nalazi resenje
Correct Answer

A. Uvek nalazi resenje, ako postoji

Explanation

The correct answer is "Uvek nalazi resenje, ako postoji." This means that a strategy is considered complete if it always finds a solution, provided that a solution exists. This implies that the strategy is able to solve any problem that has a solution.

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47.

HC algoritam - Uspon sa slucajnim ponovnim kretanjem:
- Nema direktnu vezu sa svojstvom kompletnosti
- Tezi kompletnoj pretrazi sa verovatnocom 1
- Tezi kompletnoj pretrazi sa verovatnocom 0.5
Correct Answer

A. Tezi kompletnoj pretrazi sa verovatnocom 1

Explanation

The given answer states that the HC algorithm with random restarts tends to complete the search with a probability of 1. This means that, in most cases, the algorithm will find the optimal solution or a very good solution. The use of random restarts allows the algorithm to escape local optima and continue searching for better solutions. Therefore, the HC algorithm with random restarts is likely to provide a complete search with a high probability of finding the optimal solution.

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48.

Neka se SA (algoritam simuliranog kaljenja) primenjuje za minimizaciju kriterijumske funkcije. Tada se korak u kome se kriterijumska funkcija povecava:
- Nijedno od ponudjenih odgovora
- Ne prihvata
- Prihvata sa nekom verovatnocom
- Prihvata bezuslovno
Correct Answer

A. Prihvata sa nekom verovatnocom

Explanation

In the simulated annealing algorithm, the step in which the objective function increases is accepted with some probability. This means that there is a chance that the algorithm will accept a worse solution in order to explore the search space and avoid getting stuck in local optima. Therefore, the correct answer is "Prihvata sa nekom verovatnocom" which translates to "Accepts with some probability".

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49.

Ako je heuristička funkcija u A* algoritmu oblika h(n)=C * (1/d(n)), gde je C konstanta, a d(n) dubina čvorova u grafu pretrage, pri kraju rada će algoritam imati svojstvo: ***
- Pretrage u dubinu
- Pretrage u sirinu
- Nije bitno
- Usmerene pretrage
Correct Answer

A. Pretrage u dubinu

Explanation

The given heuristic function h(n) = C * (1/d(n)), where C is a constant and d(n) is the depth of the nodes in the search graph, implies that the A* algorithm will have the property of "Pretrage u dubinu" (depth-first search) at the end of its execution. This is because the heuristic function favors nodes with smaller depths, causing the algorithm to prioritize exploring deeper paths before considering shallower ones.

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#2ai

Nalazenje optimalnih strategija pretrage u grafovima podrazumeva:

Quiz Preview

Strategija se karakterisu preko sledecih pokazatelja:

Vremenska kompleksnost algoritma se moze izraziti:

U grafu tipa stablo, koren je cvor koji:

Ako je usmerenost pretrage P=1, tada vazi:

Kod A* algoritma pretrage, u funkciji "f(n)= g(n) + h(n)", f(n) je: ***

Ukoliko za rešavanje datog problema posedujemo dodatne informacije vezane za prirodu rešavanog problema, a koje nam olakšavaju odluku o tome koji naredni čvor treba otkriti u grafu pretrage, u pitanju je:

Kod A* algoritma pretrage, u funkciji "f(n) = g(n) + h(n)", h(n) je:

Specificne informacije vezane za datu problemsku oblast koje olakšavaju procenu perspektivnosti mogućih alternativnih akcija u toku rešavanja datog problema, zovu se:

Graf se sastoji od:

Strategije pretrage definisu:

Prostorna kompleksnost se moze izraziti preko:

Ako su dve moguce heuristicke funkcije u A* algoritmu u odnosu h1(n) > h2(n), tacan je sledeci iskaz:

U grafu tipa stablo, dubina cvora tipa koren je:

Ako je tacna vrednost za h(n)=5, za neki čvor u grafu pretrage, da li je u A* algoritmu moguće da procena h(n) za taj čvor bude h(n)=6:

Ako je heuristička funkcija u A* algoritmu oblika h(n)=C * (1/d(n)), gde je C konstanta, a d(n) dubina čvorova u grafu pretrage, u početku rada će algoritam imati svojstvo:

Grane grafa mogu biti:

Ako u A* algoritmu h(n) zadovoljava uslov monotonosti, da li se može desiti promena ukazatelja u toku izvršenja programa GRApHSEARCH:

U grafovima, dohvatljivim se smatraju cvorovi do kojih:

Cvor u grafu moze istovremeno biti i roditelj i dete:

Stablo je graf kod koga vazi sledece pravilo:

U grafu tipa stablo, list je cvor koji:

Cena primene pravila u grafovima se moze izraziti:

Algoritam A* je dopustiv:

Kod A* algoritma pretrage, u funkciji "f(n) = g(n) + h(n)", g(n) je:

Da li je algoritam pretrage u sirinu A* algoritam?

Ako u A* algoritmu h(n) zadovoljava uslov monotonosti, da li se moze desiti promena ukazatelja u toku izvrsavanja programa GRApHSEARCH:

U neinformativne pretrage spadaju:

Kod neinformativne pretrage sa iterativnim produbljivanjem, u stablu sa najvecom dubinom N, ukoliko je incijlano ogranicenje dubine takodje N, ovakva pretraga se moze poistovetiti sa:

Kod neinformativne pretrage sa iterativnim produbljivanjem, u stablu sa najvecom dubinom N, ukoliko je inicijalno ogranicenje dubine 1, i u svakoj iteraciji se ogranicenje povecava za 1, ovakva pretraga se moze poistovetiti sa:

Princip SA algoritma se primenjuje u:

Lokalne pretrage po snopu:

HC algoritam - Uspon sa slucajnim ponovnim kretanjem funkcionise tako sto se:

HC algoritam - Uspon prvog izbora:

GA predstavlja:

Koje svojstvo ima algoritam koji poseduje osobinu optimalnosti: ***

Stohasticki HC algoritam:

Efikasne strategije upravljanja zahtevaju dovoljno informacija o prirodi resavanog problema, nazivaju se: ***

Cilj GA je:

Raspored hladjenja (Cooling Schedule) je:

Genetski algoritmi koriste tri operatora:

Ako se temperatura u SA algoritmu suvise sporo menja:

Proceduralna znanja su:

U SA algoritmu, parametar temperatura je: ***

Ako se temperatura u SA algoritmu suvise brzo smanjuje:

Jedna strategija je kompletna ako:

HC algoritam - Uspon sa slucajnim ponovnim kretanjem:

Neka se SA (algoritam simuliranog kaljenja) primenjuje za minimizaciju kriterijumske funkcije. Tada se korak u kome se kriterijumska funkcija povecava:

Ako je heuristička funkcija u A* algoritmu oblika h(n)=C * (1/d(n)), gde je C konstanta, a d(n) dubina čvorova u grafu pretrage, pri kraju rada će algoritam imati svojstvo: ***