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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."

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The correct answer is "Pronalazenje puta najmanje tezine" which translates to "Finding the path with the least weight." In the context of searching strategies in graphs, this means finding the path between two nodes that has the lowest total weight or cost. This is often done using algorithms such as Dijkstra's algorithm or the Bellman-Ford algorithm, which calculate the shortest path based on the weights assigned to the edges of the graph.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The probability of accepting a move in the SA algorithm depends on two factors: the temperature parameter and the change in the objective function. The temperature parameter determines the randomness of the algorithm, with higher temperatures allowing for more exploration and lower temperatures favoring exploitation. The change in the objective function determines the quality of the move, with better moves being more likely to be accepted. Therefore, the acceptance probability is influenced by both the temperature parameter and the change in the objective function.

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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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.

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.

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".

Deklarativna znanja su poseban oblik eksplicitnog znanja, koja se mogu interpretirati kao iskazi o nečemu. To znači da su to znanja koja se izražavaju u obliku tvrdnji ili izjava, a mogu se jasno interpretirati kao informacije o određenim činjenicama, konceptima ili idejama. Ova vrsta znanja se može izraziti u pisanom ili usmenom obliku i često se koristi u akademskom i stručnom kontekstu.

The correct answer is "Strategije pretrage." In production systems, strategies for searching and retrieving already tested rule sequences and the generalization of their application are referred to as search strategies. This involves searching for and selecting the appropriate rule sequences to apply based on previous experience and knowledge.

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.

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

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.

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.

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.

The correct answer is "Neinformativna strategija" because breadth-first search is a uninformed search strategy. It explores all the neighbor nodes at the present depth level before moving on to nodes at the next depth level. It does not use any information or heuristics about the problem domain to guide its search. Instead, it systematically explores the search space in a breadth-first manner, level by level, until it finds the goal state.

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.

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.

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.

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.

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.

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.

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.

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