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  • Merge method in MergeSort Algorithm .

    - by Tony
    I've seen many mergeSort implementations .Here is the version in Data Structures and Algorithms in Java (2nd Edition) by Robert Lafore : private void recMergeSort(long[] workSpace, int lowerBound,int upperBound) { if(lowerBound == upperBound) // if range is 1, return; // no use sorting else { // find midpoint int mid = (lowerBound+upperBound) / 2; // sort low half recMergeSort(workSpace, lowerBound, mid); // sort high half recMergeSort(workSpace, mid+1, upperBound); // merge them merge(workSpace, lowerBound, mid+1, upperBound); } // end else } // end recMergeSort() private void merge(long[] workSpace, int lowPtr, int highPtr, int upperBound) { int j = 0; // workspace index int lowerBound = lowPtr; int mid = highPtr-1; int n = upperBound-lowerBound+1; // # of items while(lowPtr <= mid && highPtr <= upperBound) if( theArray[lowPtr] < theArray[highPtr] ) workSpace[j++] = theArray[lowPtr++]; else workSpace[j++] = theArray[highPtr++]; while(lowPtr <= mid) workSpace[j++] = theArray[lowPtr++]; while(highPtr <= upperBound) workSpace[j++] = theArray[highPtr++]; for(j=0; j<n; j++) theArray[lowerBound+j] = workSpace[j]; } // end merge() One interesting thing about merge method is that , almost all the implementations didn't pass the lowerBound parameter to merge method . lowerBound is calculated in the merge . This is strange , since lowerPtr = mid + 1 ; lowerBound = lowerPtr -1 ; that means lowerBound = mid ; Why the author didn't pass mid to merge like merge(workSpace, lowerBound,mid, mid+1, upperBound); ? I think there must be a reason , otherwise I can't understand why an algorithm older than half a center ,and have all coincident in the such little detail.

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  • Sparse parameter selection using Genetic Algorithm

    - by bgbg
    Hello, I'm facing a parameter selection problem, which I would like to solve using Genetic Algorithm (GA). I'm supposed to select not more than 4 parameters out of 3000 possible ones. Using the binary chromosome representation seems like a natural choice. The evaluation function punishes too many "selected" attributes and if the number of attributes is acceptable, it then evaluates the selection. The problem is that in these sparse conditions the GA can hardly improve the population. Neither the average fitness cost, nor the fitness of the "worst" individual improves over the generations. All I see is slight (even tiny) improvement in the score of the best individual, which, I suppose, is a result of random sampling. Encoding the problem using indices of the parameters doesn't work either. This is most probably, due to the fact that the chromosomes are directional, while the selection problem isn't (i.e. chromosomes [1, 2, 3, 4]; [4, 3, 2, 1]; [3, 2, 4, 1] etc. are identical) What problem representation would you suggest? P.S If this matters, I use PyEvolve.

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  • Algorithm to match list of regular expressions

    - by DSII
    I have two algorithmic questions for a project I am working on. I have thought about these, and have some suspicions, but I would love to hear the community's input as well. Suppose I have a string, and a list of N regular expressions (actually they are wildcard patterns representing a subset of full regex functionality). I want to know whether the string matches at least one of the regular expressions in the list. Is there a data structure that can allow me to match the string against the list of regular expressions in sublinear (presumably logarithmic) time? This is an extension of the previous problem. Suppose I have the same situation: a string and a list of N regular expressions, only now each of the regular expressions is paired with an offset within the string at which the match must begin (or, if you prefer, each of the regular expressions must match a substring of the given string beginning at the given offset). To give an example, suppose I had the string: This is a test string and the regex patterns and offsets: (a) his.* at offset 0 (b) his.* at offset 1 The algorithm should return true. Although regex (a) does not match the string beginning at offset 0, regex (b) does match the substring beginning at offset 1 ("his is a test string"). Is there a data structure that can allow me to solve this problem in sublinear time? One possibly useful piece of information is that often, many of the offsets in the list of regular expressions are the same (i.e. often we are matching the substring at offset X many times). This may be useful to leverage the solution to problem #1 above. Thank you very much in advance for any suggestions you may have!

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  • How to gain accurate results with Painter's algorithm?

    - by pimvdb
    A while ago I asked how to determine when a face is overlapping another. The advice was to use a Z-buffer. However, I cannot use a Z-buffer in my current project and hence I would like to use the Painter's algorithm. I have no good clue as to when a surface is behind or in front of another, though. I've tried numerous methods but they all fail in edge cases, or they fail even in general cases. This is a list of sorting methods I've tried so far: Distance to midpoint of each face Average distance to each vertex of each face Average z value of each vertex Higest z value of vertices of each face and draw those first Lowest z value of vertices of each face and draw those last The problem is that a face might have a closer distance but is still further away. All these methods seem unreliable. Edit: For example, in the following image the surface with the blue point as midpoint is painted over the surface with the red point as midpoint, because the blue point is closer. However, this is because the surface of the red point is larger and the midpoint is further away. The surface with the red point should be painted over the blue one, because it is closer, whilst the midpoint distance says the opposite. What exactly is used in the Painter's algorithm to determine the order in which objects should be drawn?

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  • Triangulation A* (TA*) pathfinding algorithm

    - by hyn
    I need help understanding the Triangle A* (TA*) algorithm that is described by Demyen in his paper Efficient Triangulation-Based Pathfinding, on pages 76-81. He describes how to adapt the regular A* algorithm for triangulation, to search for other possibly more optimal paths, even after the final node is reached/expanded. Regular A* stops when the final node is expanded, but this is not always the best path when used in a triangulated graph. This is exactly the problem I'm having. The problem is illustrated on page 78, Figure 5.4: I understand how to calculate the g and h values presented in the paper (page 80). And I think the search stop condition is: if (currentNode.fCost > shortestDistanceFound) { // stop break; } where currentNode is the search node popped from the open list (priority queue), which has the lowest f-score. shortestDistanceFound is the actual distance of the shortest path found so far. But how do I exclude the previously found paths from future searches? Because if I do the search again, it will obviously find the same path. Do I reset the closed list? I need to modify something, but I don't know what it is I need to change. The paper lacks pseudocode, so that would be helpful.

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  • need explanation on amortization in algorithm

    - by Pradeep
    I am a learning algorithm analysis and came across a analysis tool for understanding the running time of an algorithm with widely varying performance which is called as amortization. The autor quotes " An array with upper bound of n elements, with a fixed bound N, on it size. Operation clear takes O(n) time, since we should dereference all the elements in the array in order to really empty it. " The above statement is clear and valid. Now consider the next content: "Now consider a series of n operations on an initially empty array. if we take the worst case viewpoint, the running time is O(n^2), since the worst case of a sigle clear operation in the series is O(n) and there may be as many as O(n) clear operations in the series." From the above statement how is the time complexity O(n^2)? I did not understand the logic behind it. if 'n' operations are performed how is it O(n ^2)? Please explain what the autor is trying to convey..

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  • How does flocking algorithm work?

    - by Chan
    I read and understand the basic of flocking algorithm. Basically, we need to have 3 behaviors: 1. Cohesion 2. Separation 3. Alignment From my understanding, it's like a state machine. Every time we do an update (then draw), we check all the constraints on both three behaviors. And each behavior returns a Vector3 which is the "correct" orientation that an object should transform to. So my initial idea was /// <summary> /// Objects stick together /// </summary> /// <returns></returns> private Vector3 Cohesion() { Vector3 result = new Vector3(0.0f, 0.0f, 0.0f); return result; } /// <summary> /// Object align /// </summary> /// <returns></returns> private Vector3 Align() { Vector3 result = new Vector3(0.0f, 0.0f, 0.0f); return result; } /// <summary> /// Object separates from each others /// </summary> /// <returns></returns> private Vector3 Separate() { Vector3 result = new Vector3(0.0f, 0.0f, 0.0f); return result; } Then I search online for pseudocode but many of them involve velocity and acceleration plus other stuffs. This part confused me. In my game, all objects move at constant speed, and they have one leader. So can anyone share me an idea how to start on implement this flocking algorithm? Also, did I understand it correctly? (I'm using XNA 4.0)

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  • Algorithm to generate multifaced cube?

    - by OnePie
    Are there any elegant soloution to generate a simple-six sided cube, where each cube is made out of more than one face? The method I have used ended up a horrible and complicated mess of logic that is imopssible to follow and most likely to maintain. The algorithm should not generate reduntant vertices, and should output the indice list for the mesh as well. The reason I need this is that the cubes vertices will be deformed depending on various factors, meaning that a simple six-faced cube will nto do.

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  • How to utilize miniMax algorithm in Checkers game

    - by engineer
    I am sorry...as there are too many articles about it.But I can't simple get this. I am confused in the implementation of AI. I have generated all possible moves of computer's type pieces. Now I can't decide the flow. Whether I need to start a loop for the possible moves of each piece and assign score to it.... or something else is to be done. Kindly tell me the proper flow/algorithm for this. Thanks

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  • Ideas for attack damage algorithm (language irrelevant)

    - by Dillon
    I am working on a game and I need ideas for the damage that will be done to the enemy when your player attacks. The total amount of health that the enemy has is called enemyHealth, and has a value of 1000. You start off with a weapon that does 40 points of damage (may be changed.) The player has an attack stat that you can increase, called playerAttack. This value starts off at 1, and has a possible max value of 100 after you level it up many times and make it farther into the game. The amount of damage that the weapon does is cut and dry, and subtracts 40 points from the total 1000 points of health every time the enemy is hit. But what the playerAttack does is add to that value with a percentage. Here is the algorithm I have now. (I've taken out all of the gui, classes, etc. and given the variables very forward names) double totalDamage = weaponDamage + (weaponDamage*(playerAttack*.05)) enemyHealth -= (int)totalDamage; This seemed to work great for the most part. So I statrted testing some values... //enemyHealth ALWAYS starts at 1000 weaponDamage = 50; playerAttack = 30; If I set these values, the amount of damage done on the enemy is 125. Seemed like a good number, so I wanted to see what would happen if the players attack was maxed out, but with the weakest starting weapon. weaponDamage = 50; playerAttack = 100; the totalDamage ends up being 300, which would kill an enemy in just a few hits. Even with your attack that high, I wouldn't want the weakest weapon to be able to kill the enemy that fast. I thought about adding defense, but I feel the game will lose consistency and become unbalanced in the long run. Possibly a well designed algorithm for a weapon decrease modifier would work for lower level weapons or something like that. Just need a break from trying to figure out the best way to go about this, and maybe someone that has experience with games and keeping the leveling consistent could give me some ideas/pointers.

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  • Algorithm to map an area [on hold]

    - by user37843
    I want to create a crawler that starts in a room and from that room to move North,East,West and South until there aren't any new rooms to visit. I don't want to have duplicates and the output format per line to be something like this: current room, neighbour 1, neighbour 2 ... and in the end to apply BFS algorithm to find the shortest path between 2 rooms. Can anyone offer me some suggestion what to use? Thanks

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  • Algorithm for querying linearly through a non-linear list of questions

    - by JoshLeaves
    For a multiplayers trivia game, I need to supply my users with a new quizz in a desired subject (Science, Maths, Litt. and such) at the start of every game. I've generated about 5K quizzes for each subject and filled my database with them. So my 'Quizzes' database looks like this: |ID |Subject |Question +-----+------------+---------------------------------- | 23 |Science | What's water? | 42 |Maths | What's 2+2? | 99 |Litt. | Who wrote "Pride and Prejudice"? | 123 |Litt. | Who wrote "On The Road"? | 146 |Maths | What's 2*2? | 599 |Science | You know what's cool? |1042 |Maths | What's the Fibonacci Sequence? |1056 |Maths | What's 42? And so on... (Much more detailed/complex but I'll keep the exemple simple) As you can see, due to technical constraints (MongoDB), my IDs are not linear but I can use them as an increasing suite. So far, my algorithm to ensure two users get a new quizz when they play together is the following: // Take the last played quizzes by P1 and P2 var q_one = player_one.getLastPlayedQuizz('Maths'); var q_two = player_two.getLastPlayedQuizz('Maths'); // If both of them never played in the subject, return first quizz in the list if ((q_one == NULL) && (q_two == NULL)) return QuizzDB.findOne({subject: 'Maths'}); // If one of them never played, play the next quizz for the other player // This quizz is found by asking for the first quizz in the desired subject where // the ID is greater than the last played quizz's ID (if the last played quizz ID // is 42, this will return 146 following the above example database) if (q_one == NULL) return QuizzDB.findOne({subject: 'Maths', ID > q_two}); if (q_two == NULL) return QuizzDB.findOne({subject: 'Maths', ID > q_one}); // And if both of them have a lastPlayedQuizz, we return the next quizz for the // player whose lastPlayedQuizz got the higher ID if (q_one > q_two) return QuizzDB.findOne({subject: 'Maths', ID > q_one}); else return QuizzDB.findOne({subject: 'Maths', ID > q_two}); Now here comes the real problem: Once I get to the end of my database (let's say, P1's last played quizz in 'Maths' is 1056, P2's is 146 and P3 is 1042), following my algorithm, P1's ID is the highest so I ask for the next question in 'Maths' where ID is superior to 1056. There is nothing, so I roll back to the beginning of my quizz list (with a random skipper to avoid having the first question always show up). P1 and P2's last played will then be 42 and they will start fresh from the beginning of the list. However, if P1 (42) plays against P3 (1042), the resulting ID will be 1056...which P1 already played two games ago. Basically, players who just "rolled back" to the beginning of the list will be brought back to the end of the list by players who still haven't rolled back. The rollback WILL happen in the end, but it'll take time and there'll be a "bottleneck" at the beginning and at the end. Thus my question: What would be the best algorith to avoid this bottleneck and ensure players don't get stuck endlessly on the same quizzes? Also bear in mind that I've got some technical constraints: I can't get a random question in a subject (ie: no "QuizzDB.findOne({subject: 'Maths'}).skip(random());"). It's cool to skip on one to twenty records, but the MongoDB documentation warns against skipping too many documents. I would like to avoid building an array of every quizz played by each player and find the next non-played in the database with a $nin. Thanks for your help

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  • Search algorithm (with a sort algorithm already implemented)

    - by msr
    Hello, Im doing a Java application and Im facing some doubts in which concerns performance. I have a PriorityQueue which guarantees me the element removed is the one with greater priority. That PriorityQueue has instances of class Event (which implements Comparable interface). Each Event is associated with a Entity. The size of that priorityqueue could be huge and very frequently I will have to remove events associated to an entity. Right now Im using an iterator to run all the priorityqueue. However Im finding it heavy and I wonder if there are better alternatives to search and remove events associated with an entity "xpto". Any suggestions? Thanks!

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  • Help:Graph contest problem: maybe a modified Dijkstra or another alternative algorithm

    - by newba
    Hi you all, I'm trying to do this contest exercise about graphs: XPTO is an intrepid adventurer (a little too temerarious for his own good) who boasts about exploring every corner of the universe, no matter how inhospitable. In fact, he doesn't visit the planets where people can easily live in, he prefers those where only a madman would go with a very good reason (several millions of credits for instance). His latest exploit is trying to survive in Proxima III. The problem is that Proxima III suffers from storms of highly corrosive acids that destroy everything, including spacesuits that were especially designed to withstand corrosion. Our intrepid explorer was caught in a rectangular area in the middle of one of these storms. Fortunately, he has an instrument that is capable of measuring the exact concentration of acid on each sector and how much damage it does to his spacesuit. Now, he only needs to find out if he can escape the storm. Problem The problem consists of finding an escape route that will allow XPTOto escape the noxious storm. You are given the initial energy of the spacesuit, the size of the rectangular area and the damage that the spacesuit will suffer while standing in each sector. Your task is to find the exit sector, the number of steps necessary to reach it and the amount of energy his suit will have when he leaves the rectangular area. The escape route chosen should be the safest one (i.e., the one where his spacesuit will be the least damaged). Notice that Rodericus will perish if the energy of his suit reaches zero. In case there are more than one possible solutions, choose the one that uses the least number of steps. If there are at least two sectors with the same number of steps (X1, Y1) and (X2, Y2) then choose the first if X1 < X2 or if X1 = X2 and Y1 < Y2. Constraints 0 < E = 30000 the suit's starting energy 0 = W = 500 the rectangle's width 0 = H = 500 rectangle's height 0 < X < W the starting X position 0 < Y < H the starting Y position 0 = D = 10000 the damage sustained in each sector Input The first number given is the number of test cases. Each case will consist of a line with the integers E, X and Y. The following line will have the integers W and H. The following lines will hold the matrix containing the damage D the spacesuit will suffer whilst in the corresponding sector. Notice that, as is often the case for computer geeks, (1,1) corresponds to the upper left corner. Output If there is a solution, the output will be the remaining energy, the exit sector's X and Y coordinates and the number of steps of the route that will lead Rodericus to safety. In case there is no solution, the phrase Goodbye cruel world! will be written. Sample Input 3 40 3 3 7 8 12 11 12 11 3 12 12 12 11 11 12 2 1 13 11 11 12 2 13 2 14 10 11 13 3 2 1 12 10 11 13 13 11 12 13 12 12 11 13 11 13 12 13 12 12 11 11 11 11 13 13 10 10 13 11 12 8 3 4 7 6 4 3 3 2 2 3 2 2 5 2 2 2 3 3 2 1 2 2 3 2 2 4 3 3 2 2 4 1 3 1 4 3 2 3 1 2 2 3 3 0 3 4 10 3 4 7 6 3 3 1 2 2 1 0 2 2 2 4 2 2 5 2 2 1 3 0 2 2 2 2 1 3 3 4 2 3 4 4 3 1 1 3 1 2 2 4 2 2 1 Sample Output 12 5 1 8 Goodbye cruel world! 5 1 4 2 Basically, I think we have to do a modified Dijkstra, in which the distance between nodes is the suit's energy (and we have to subtract it instead of suming up like is normal with distances) and the steps are the ....steps made along the path. The pos with the bester binomial (Energy,num_Steps) is our "way out". Important : XPTO obviously can't move in diagonals, so we have to cut out this cases. I have many ideas, but I have such a problem implementing them... Could someone please help me thinking about this with some code or, at least, ideas? Am I totally wrong?

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  • What problems have you solved using genetic algorithms/genetic programming?

    - by knorv
    Genetic algorithms (GA) and genetic programming (GP) are interesting areas of research. I'd like to know about specific problems you - the SO reader - have solved using GA/GP and what libraries/frameworks you used if you didn't roll your own. Questions: What problems have you used GA/GP to solve? What libraries/frameworks did you use? I'm looking for first-hand experiences, so please do not answer unless you have that.

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  • Best Fit Scheduling Algorithm

    - by Teegijee
    I'm writing a scheduling program with a difficult programming problem. There are several events, each with multiple meeting times. I need to find an arrangement of meeting times such that each schedule contains any given event exactly once, using one of each event's multiple meeting times. Obviously I could use brute force, but that's rarely the best solution. I'm guessing this is a relatively basic computer science problem, which I'll learn about once I am able to start taking computer science classes. In the meantime, I'd prefer any links where I could read up on this, or even just a name I could Google.

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  • Graph colouring algorithm: typical scheduling problem

    - by newba
    Hi, I'm training code problems like UvA and I have this one in which I have to, given a set of n exams and k students enrolled in the exams, find whether it is possible to schedule all exams in two time slots. Input Several test cases. Each one starts with a line containing 1 < n < 200 of different examinations to be scheduled. The 2nd line has the number of cases k in which there exist at least 1 student enrolled in 2 examinations. Then, k lines will follow, each containing 2 numbers that specify the pair of examinations for each case above. (An input with n = 0 will means end of the input and is not to be processed). Output: You have to decide whether the examination plan is possible or not for 2 time slots. Example: Input: 3 3 0 1 1 2 2 0 9 8 0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 Ouput: NOT POSSIBLE. POSSIBLE. I think the general approach is graph colouring, but I'm really a newb and I may confess that I had some trouble understanding the problem. Anyway, I'm trying to do it and then submit it. Could someone please help me doing some code for this problem? I will have to handle and understand this algo now in order to use it later, over and over. I prefer C or C++, but if you want, Java is fine to me ;) Thanks in advance

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  • Novel fitness measure for evolutionary image matching simulation

    - by Nick Johnson
    I'm sure many people have already seen demos of using genetic algorithms to generate an image that matches a sample image. You start off with noise, and gradually it comes to resemble the target image more and more closely, until you have a more-or-less exact duplicate. All of the examples I've seen, however, use a fairly straightforward pixel-by-pixel comparison, resulting in a fairly predictable 'fade in' of the final image. What I'm looking for is something more novel: A fitness measure that comes closer to what we see as 'similar' than the naive approach. I don't have a specific result in mind - I'm just looking for something more 'interesting' than the default. Suggestions?

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  • Algorithm on trajectory analysis.

    - by Arman
    Hello, I would like to analyse the trajectory data based on given templates. I need to stack the similar trajectories together. The data is a set of coordinates xy,xy,xy and the templates are again the lines defined by the set of control points. I don't know to what direction to go, maybe to Neural Networks or pattern recognition? Could you please advace me page, book or library to start with? kind regards Arman. PS. Is it the right place to ask the question?

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  • Shortest Path algorithm of a different kind

    - by Ram Bhat
    Hey guys, Lets say you have a grid like this (made randomly) Now lets say you have a car starting randomly from one of the while boxes, what would be the shortest path to go through each one of the white boxes? you can visit each white box as many times as you want and cant Jump over the black boxes. The black boxes are like walls. In simple words you can move from white box to white box only.. You can move in any direction, even diagonally.

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  • Genetic algorithm resource

    - by Siblja
    Lately I'm interested in a topic of genetic algorithms, but i couldn't find any good resource. If you know any good resource, book or a site i would appreciate it. I have solid knowledge of algorithms and A.I. but im looking for something with good introduction in genetic programing.

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  • Algorithm to make groups of units

    - by M28
    In Age of Mythology and some other strategy games, when you select multiple units and order them to move to some place, they make a "group" when they reach the desired location: I have a Vector with several sprites, which are the selected units, the variables tarX and tarY are the target x and y. I just want an example, so you can just set the x and y position and I can adapt it to my code. Also, I would like to ask that the algorithm calls "isWalkable" for the x and y position, to determine if it's a valid position for each unit.

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  • Factors to consider when building an algorithm for gun recoil

    - by Nate Bross
    What would be a good algorithm for calculating the recoil of a shooting guns cross-hairs? What I've got now, is something like this: Define min/max recoil based on weapon size Generate random number of "delta" movement Apply random value to X, Y, or both of cross-hairs (only "up" on the Y axis) Multiply new delta based on time from the previous shot (more recoil for full-auto) What I'm worried about is that this feels rather predicable, what other factors should one take into account when building recoil? While I'd like it to be somewhat predictable, I'd also like to keep players on their toes. I'm thinking about increasing the min/max recoil values by a large amount (relatively) and adding a weighting, so large recoils will be more rare -- it seems like a lot of effort to go into something I felt would be simple. Maybe this is just something that needs to be fine-tuned with additional playtesting, and more playtesters? I think that it's important to note, that the recoil will be a large part of the game, and is a key factor in the game being fun/challenging or not.

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  • How meaningful is the Big-O time complexity of an algorithm?

    - by james creasy
    Programmers often talk about the time complexity of an algorithm, e.g. O(log n) or O(n^2). Time complexity classifications are made as the input size goes to infinity, but ironically infinite input size in computation is not used. Put another way, the classification of an algorithm is based on a situation that algorithm will never be in: where n = infinity. Also, consider that a polynomial time algorithm where the exponent is huge is just as useless as an exponential time algorithm with tiny base (e.g., 1.00000001^n) is useful. Given this, how much can I rely on the Big-O time complexity to advise choice of an algorithm?

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