Questions tagged [search]

For questions involving search algorithms and their use in artificial intelligence

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55 views

Understanding the proof that A* search is optimal

I don't understand the proof that $A^*$ is optimal. The proof is by contradiction: Assume $A^*$ returns $p$ but there exists a $p'$ that is cheaper. When $p$ is chosen from the frontier, assume $...
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1answer
25 views

How to transform a PDDL to search?

I have a question about search and planning: I still haven't understood the difference from the two, but they seem very similar to me; here is a question I am struggling with: "Having formulated a ...
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2answers
55 views

Why is a mix of greedy and random usually “best” for stochastic local search?

I read that a mix of "greedy" and "random" are ideal for stochastic local search (SLS), but I'm not sure why. It mentioned that the greedy finds the local minima and the randomness avoids getting ...
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0answers
29 views

Can AC-3 algorithm solve N-Queens problem?

I am building CSP NQueens solver and apply the AC-3 algorithm.But,the domain reduction doesn't occur and gets more search time.How does it happen?Is it a nature of AC-3 algorithm?
2
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1answer
24 views

Proof Branch and Bound always finds optimal path in a graph?

I've been studying Branch and Bound's graph algorithm and I hear it always finds the optimal path because it uses previously found solutions to find others, but I haven't been able to find a proof on ...
2
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1answer
53 views

Using graph searching to solve peg solitaire?

Problem: I've been reading research papers on how to solve a peg solitaire using graph searching, but all the papers kind of assume you know how to do the reduction(polynomial time conversion) from ...
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1answer
20 views

what are the similarity measure use for both continuous and categorical data?

I have searched but found that some similarity measures are for continuous data and some are for categorical data. But i want to know the similarity measures which are use for both data, continuous ...
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1answer
84 views

How do I choose the search algorithm for a particular task?

How do I choose the search algorithm for a particular task? Which criteria should I take into account?
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2answers
52 views

How can the A* algorithm be optimized?

How can the A* algorithm be optimized? Any references that shows the optimization of A* algorithm are also appreciated.
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1answer
53 views

Why is informed search more efficient than uninformed search?

Why does informed search more efficiently finds a solution than an uninformed search?
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2answers
120 views

What is the difference between search and learning?

I came across an article, The Bitter Truth, via the Two Minute Papers YouTube Channel. Rich Sutton says... One thing that should be learned from the bitter lesson is the great power of general ...
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0answers
38 views

Is the minimum and maximum of a set of admissible and consistent heuristics also consistent and admissible?

Let's suppose I have a set of heuristics $S$ = {$h_1, h_2, ..., h_n$}. If all heuristics in $S$ are admissible, does that mean that a heuristic that takes the $MIN(S)$ (or $MAX$ for that matter) is ...
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1answer
46 views

How could we solve the TSP using an hill-climbing approach?

How could we solve the TSP using an hill-climbing approach?
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1answer
26 views

What are the common techniques one could use to deal with collisions in a Transposition Table?

Consider an iterative deepening search using a transposition table. Whenever the transposition table is full, what are common strategies applied to replace entries in the table? I'm aware of two ...
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0answers
17 views

In which situation hill climbing searching will be more appropriate?

There are various heuristic search algorithms, like hill climbing, greedy search, A* algorithm, but when it is best preferred to use hill climbing?
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1answer
45 views

How do I model the blocked N queens problem as a search problem?

The blocked N-queens is a variant of the N-queens problem. In the blocked N-queens problem, we also have a NxN chess board and N queens. Each square can hold at most one queen. Some squares on the ...
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2answers
210 views

Difference between Graph Search and Tree Search

First of all, there is a lot of misunderstanding about the Graph search and Tree search. The difference between these two is not about Graph and Tree. They have two different algorithms. You can find ...
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2answers
188 views

What is the difference between search and planning?

I'm studying Artificial Intelligence. A Modern Approach, Stuart Russell, Peter Norvig, specifically about search and planning arguments. I don't understand the difference between the two terms. I was ...
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0answers
110 views

How does DARTS compare to ENAS?

How does DARTS compare to ENAS? Which one is better or what advantages does they each have? Links: DARTS: Differentiable Architecture Search Efficient Neural Architecture Search via Parameter ...
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3answers
493 views

Can someone help me to understand the alpha-beta pruning algorithm?

I understand the minimax algorithm, but I am unable to understand deeply the minimax algorithm with alpha-beta pruning, even after having looked up several sources (on the web) and having tried to ...
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2answers
139 views

When should I use simulated annealing as opposed to a genetic algorithm?

What kind of problems is simulated annealing better suited for compared to genetic algorithms? From my experience, genetic algorithms seem to perform better than simulated annealing for most problems....
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1answer
43 views

What kind of search method is A*?

What kind of search method is A*? Explain to me with an example.
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2answers
404 views

What are examples of daily life applications that use simulated annealing?

In AIMA, 3rd Edition on Page 125, Simulated Annealing is described as: Hill-climbing algorithm that never makes “downhill” moves toward states with lower value (or higher cost) is guaranteed to be ...
4
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1answer
56 views

How do we find the length (depth) of the game tic-tac-toe in adversarial search?

When we perform the tic-tac-toe game using adversarial search I know how make a tree. Is there a way to find the depth of the tree; which level is the last level?
2
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1answer
105 views

Why does hill climbing algorithm only produce a local maximum?

Apparently, the hill climbing algorithm just produces a local maximum, and not necessarily a global optimum. It's stuck on a local maximum. Why does hill climbing algorithm only produce a local ...
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1answer
450 views

Why we use LIFO(Last in First Out) queue in depth first search?

As, we use FIFO(First In First Out) queue in breadth search algorithm but in depth first search we use LIFO.Why we use LIFO instead of FIFO in depth first search?
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1answer
1k views

How do I show that uniform-cost search is a special case of A*?

How do I show that uniform-cost search is a special case of A*? How do I prove this?
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1answer
56 views

Is the parent cost in A* added in every extended child?

How do we determine the cost of the parent path to its child in A* ("A star") search?
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1answer
75 views

What is the basic purpose of local search methods?

I read about the hill climbing algorithms, the simulating annealing algorithm, but I am confused. What is the basic purpose of local search methods?
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1answer
188 views

Breadth first search VS recursive best first search?

What is the difference between breadth first search and recursive best first search ? How can I describe the key difference between them?
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2answers
1k views

What is an objective function?

Local search algorithms are useful for solving pure optimization problems, in which the aim is to find the best state according to an objective function. My question is what is the objective function ?...
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2answers
4k views

What are the limitations of the hill climbing algorithm and how to overcome them?

What are the limitations of the hill climbing algorithm? How can we overcome these limitations?
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1answer
981 views

How is simulated annealing better than hill climbing methods?

In hill climbing methods, at each step, the current solution is replaced with the best neighbour (that is, the neighbour with highest/smallest value). In simulated annealing, "downhills" moves are ...
2
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1answer
406 views

What are the differences between uniform-cost search and greedy best-first search?

What are the differences between the uniform-cost search (UCS) and greedy best-first search (GBFS) algorithms? How would you convert a UCS into a GBFS?
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1answer
4k views

What are the practical differences between A* and greedy best-first search?

What are the differences between the A* algorithm and the greedy best-first search algorithm? Which one should I use? Which algorithm is the better one, and why?
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1answer
1k views

How is iterative deepening A* better than A*?

The iterative deepening A* search is an algorithm that can find the shortest path between a designated start node and any member of a set of goals. The A* algorithm evaluates nodes by combining the ...
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2answers
122 views

Which Algorithm is best for Robots? [closed]

I am a student and I study Algorithms like tree search algorithm graph search algorithm Then apply BFS DFS UCS IDS DLS Where are all these algorithms are used? I know there is a long list of ...
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2answers
3k views

How does the uniform-cost search algorithm work?

What is the uniform-cost search algorithm? How does it work? I would appreciate to see a graphical execution of the algorithm. How does the "frontier" evolve in the case of UCS?
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2answers
1k views

When should the iterative deepening search and the depth-limited search be used?

When should the iterative deepening search (IDS), also called iterative deepening depth-first search (IDDFS), and the depth-limited search be used?
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2answers
4k views

Greedy best first Search Algorithm vs A* search Algorithm

Greedy best first search Algorithm take the history and then check value ans then reach to goal. In A* search Algorithm take history and also cost then calculate value then reach to goal. When we ...
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2answers
78 views

Any problems/games/puzzles in which exhaustive search cannot show that a solution does not exist?

Introduction Exhaustive search is a method in AI planning to find a solution for so called Constraint Satisfaction Problems. (CSP). That are problems which have some conditions to fulfill and the ...
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1answer
94 views

Transposition table is only used for roughly 17% of the nodes - is this expected?

I'm making a Connect Four game using the typical minimax + alpha-beta pruning algorithms. I just implemented a Transposition Table, but my tests tell me the TT only helps 17% of the time. By this I ...
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2answers
790 views

What heuristic to use when doing A* search with multiple targets?

The problem of multi-goal path planning was introduced in an ICRA paper in the year 2011: “Multi-goal planning is a task which arises in many robotics applications. It combines the challenging ...
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1answer
67 views

In the implementation of AI programming, does DFS always stop when it has found the leftmost solution?

I'm a fresh learner of AI. I was told that depth-first search is not an optimal searching algorithm since "it finds the 'leftmost' solution, regardless of depth or cost". Therefore, does it mean that ...
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2answers
290 views

More effective way to improve the heuristics of an AI… evolution or testing between thousands of pre-determined sets of heuristics?

I'm making a Connect Four game where my engine uses Minimax with Alpha-Beta pruning to search. Since Alpha-Beta pruning is much more effective when it looks at the best moves first (since then it can ...
0
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1answer
57 views

Which is more important, doubt or reinforcement?

Reinforcement? We hear much about reinforcement, which is, in my opinion a poor choice of a term to describe a type of artificial network that continues to acquire or improve its behavioral ...
4
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1answer
488 views

Exploration Strategies for Reinforcement Learning w/ Continuous Action Space

I'm building a deep neural network to serve as the policy estimator in an Actor-Critic reinforcement learning algorithm for a continuing (not episodic) case. I'm trying to determine how to explore ...
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1answer
851 views

How do you calculate the heuristic value in this specific case?

The A* algorithm uses the "evaluation function" $f(n) = g(n) + h(n)$, where $g(n)$ = cost of the path from the start node to node $n$ $h(n)$ = estimated cost of the cheapest path from $n$ to the ...
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1answer
81 views

AI to recognize keyword in a phrase within a context

I am building a search engine and I am looking for an open source AI algorithm to recognize the keyword in a search phrase within a particular context. So if a user passes something in the line of <...
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3answers
841 views

Why does Monte Carlo work when a real opponent's behavior may not be random

I am learning about Monte Carlo algorithms and struggling to understand the following: If simulations are based on random moves, how can the modeling of the opponent's behavior work well? For ...