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  • Advanced System Monitor/Task Manager?

    - by instanceofTom
    When using kubuntu I noticed that the standard task manager/system monitor was a bit more capable than gnome-system-monitor, is there a more advanced system/task monitor for ubuntu that is based on gnome opposed to KDE? Specifically the features from the Kubuntu task manager that I am looking for are the ability to control the I/O priority of individual processes (not just their nice), and the ability to control the I/O scheduling algorithm ( round-robin, FIFO, etc). What are my options?

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  • Data structures in functional programming

    - by pwny
    I'm currently playing with LISP (particularly Scheme and Clojure) and I'm wondering how typical data structures are dealt with in functional programming languages. For example, let's say I would like to solve a problem using a graph pathfinding algorithm. How would one typically go about representing that graph in a functional programming language (primarily interested in pure functional style that can be applied to LISP)? Would I just forget about graphs altogether and solve the problem some other way?

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  • Is there any hueristic to polygonize a closed 2d-raster shape with n triangles?

    - by Arthur Wulf White
    Lets say we have a 2d image black on white that shows a closed geometric shape. Is there any (not naive brute force) algorithm that approximates that shape as closely as possible with n triangles? If you want a formal definition for as closely as possible: Approximate the shape with a polygon that when rendered into a new 2d image will match the largest number of pixels possible with the original image.

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  • DTracing TCP congestion control

    - by user12820842
    In a previous post, I showed how we can use DTrace to probe TCP receive and send window events. TCP receive and send windows are in effect both about flow-controlling how much data can be received - the receive window reflects how much data the local TCP is prepared to receive, while the send window simply reflects the size of the receive window of the peer TCP. Both then represent flow control as imposed by the receiver. However, consider that without the sender imposing flow control, and a slow link to a peer, TCP will simply fill up it's window with sent segments. Dealing with multiple TCP implementations filling their peer TCP's receive windows in this manner, busy intermediate routers may drop some of these segments, leading to timeout and retransmission, which may again lead to drops. This is termed congestion, and TCP has multiple congestion control strategies. We can see that in this example, we need to have some way of adjusting how much data we send depending on how quickly we receive acknowledgement - if we get ACKs quickly, we can safely send more segments, but if acknowledgements come slowly, we should proceed with more caution. More generally, we need to implement flow control on the send side also. Slow Start and Congestion Avoidance From RFC2581, let's examine the relevant variables: "The congestion window (cwnd) is a sender-side limit on the amount of data the sender can transmit into the network before receiving an acknowledgment (ACK). Another state variable, the slow start threshold (ssthresh), is used to determine whether the slow start or congestion avoidance algorithm is used to control data transmission" Slow start is used to probe the network's ability to handle transmission bursts both when a connection is first created and when retransmission timers fire. The latter case is important, as the fact that we have effectively lost TCP data acts as a motivator for re-probing how much data the network can handle from the sending TCP. The congestion window (cwnd) is initialized to a relatively small value, generally a low multiple of the sending maximum segment size. When slow start kicks in, we will only send that number of bytes before waiting for acknowledgement. When acknowledgements are received, the congestion window is increased in size until cwnd reaches the slow start threshold ssthresh value. For most congestion control algorithms the window increases exponentially under slow start, assuming we receive acknowledgements. We send 1 segment, receive an ACK, increase the cwnd by 1 MSS to 2*MSS, send 2 segments, receive 2 ACKs, increase the cwnd by 2*MSS to 4*MSS, send 4 segments etc. When the congestion window exceeds the slow start threshold, congestion avoidance is used instead of slow start. During congestion avoidance, the congestion window is generally updated by one MSS for each round-trip-time as opposed to each ACK, and so cwnd growth is linear instead of exponential (we may receive multiple ACKs within a single RTT). This continues until congestion is detected. If a retransmit timer fires, congestion is assumed and the ssthresh value is reset. It is reset to a fraction of the number of bytes outstanding (unacknowledged) in the network. At the same time the congestion window is reset to a single max segment size. Thus, we initiate slow start until we start receiving acknowledgements again, at which point we can eventually flip over to congestion avoidance when cwnd ssthresh. Congestion control algorithms differ most in how they handle the other indication of congestion - duplicate ACKs. A duplicate ACK is a strong indication that data has been lost, since they often come from a receiver explicitly asking for a retransmission. In some cases, a duplicate ACK may be generated at the receiver as a result of packets arriving out-of-order, so it is sensible to wait for multiple duplicate ACKs before assuming packet loss rather than out-of-order delivery. This is termed fast retransmit (i.e. retransmit without waiting for the retransmission timer to expire). Note that on Oracle Solaris 11, the congestion control method used can be customized. See here for more details. In general, 3 or more duplicate ACKs indicate packet loss and should trigger fast retransmit . It's best not to revert to slow start in this case, as the fact that the receiver knew it was missing data suggests it has received data with a higher sequence number, so we know traffic is still flowing. Falling back to slow start would be excessive therefore, so fast recovery is used instead. Observing slow start and congestion avoidance The following script counts TCP segments sent when under slow start (cwnd ssthresh). #!/usr/sbin/dtrace -s #pragma D option quiet tcp:::connect-request / start[args[1]-cs_cid] == 0/ { start[args[1]-cs_cid] = 1; } tcp:::send / start[args[1]-cs_cid] == 1 && args[3]-tcps_cwnd tcps_cwnd_ssthresh / { @c["Slow start", args[2]-ip_daddr, args[4]-tcp_dport] = count(); } tcp:::send / start[args[1]-cs_cid] == 1 && args[3]-tcps_cwnd args[3]-tcps_cwnd_ssthresh / { @c["Congestion avoidance", args[2]-ip_daddr, args[4]-tcp_dport] = count(); } As we can see the script only works on connections initiated since it is started (using the start[] associative array with the connection ID as index to set whether it's a new connection (start[cid] = 1). From there we simply differentiate send events where cwnd ssthresh (congestion avoidance). Here's the output taken when I accessed a YouTube video (where rport is 80) and from an FTP session where I put a large file onto a remote system. # dtrace -s tcp_slow_start.d ^C ALGORITHM RADDR RPORT #SEG Slow start 10.153.125.222 20 6 Slow start 138.3.237.7 80 14 Slow start 10.153.125.222 21 18 Congestion avoidance 10.153.125.222 20 1164 We see that in the case of the YouTube video, slow start was exclusively used. Most of the segments we sent in that case were likely ACKs. Compare this case - where 14 segments were sent using slow start - to the FTP case, where only 6 segments were sent before we switched to congestion avoidance for 1164 segments. In the case of the FTP session, the FTP data on port 20 was predominantly sent with congestion avoidance in operation, while the FTP session relied exclusively on slow start. For the default congestion control algorithm - "newreno" - on Solaris 11, slow start will increase the cwnd by 1 MSS for every acknowledgement received, and by 1 MSS for each RTT in congestion avoidance mode. Different pluggable congestion control algorithms operate slightly differently. For example "highspeed" will update the slow start cwnd by the number of bytes ACKed rather than the MSS. And to finish, here's a neat oneliner to visually display the distribution of congestion window values for all TCP connections to a given remote port using a quantization. In this example, only port 80 is in use and we see the majority of cwnd values for that port are in the 4096-8191 range. # dtrace -n 'tcp:::send { @q[args[4]-tcp_dport] = quantize(args[3]-tcps_cwnd); }' dtrace: description 'tcp:::send ' matched 10 probes ^C 80 value ------------- Distribution ------------- count -1 | 0 0 |@@@@@@ 5 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 0 512 | 0 1024 | 0 2048 |@@@@@@@@@ 8 4096 |@@@@@@@@@@@@@@@@@@@@@@@@@@ 23 8192 | 0

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  • Height Map Mapping to "Chunked" Quadrilateralized Spherical Cube

    - by user3684950
    I have been working on a procedural spherical terrain generator for a few months which has a quadtree LOD system. The system splits the six faces of a quadrilateralized spherical cube into smaller "quads" or "patches" as the player approaches those faces. What I can't figure out is how to generate height maps for these patches. To generate the heights I am using a 3D ridged multi fractals algorithm. For now I can only displace the vertices of the patches directly using the output from the ridged multi fractals. I don't understand how I generate height maps that allow the vertices of a terrain patch to be mapped to pixels in the height map. The only thing I can think of is taking each vertex in a patch, plug that into the RMF and take that position and translate into u,v coordinates then determine the pixel position directly from the u,v coordinates and determine the grayscale color based on the height. I feel as if this is the right approach but there are a few other things that may further complicate my problem. First of all I intend to use "height maps" with a pixel resolution of 192x192 while the vertex "resolution" of each terrain patch is only 16x16 - meaning that I don't have any vertices to sample for the RMF for most of the pixels. The main reason the height map resolution is higher so that I can use it to generate a normal map (otherwise the height maps serve little purpose as I can just directly displace vertices as I currently am). I am pretty much following this paper very closely. This is, essentially, the part I am having trouble with. Using the cube-to-sphere mapping and the ridged multifractal algorithm previously described, a normalized height value ([0, 1]) is calculated. Using this height value, the terrain position is calculated and stored in the first three channels of the positionmap (RGB) – this will be used to calculate the normalmap. The fourth channel (A) is used to store the height value itself, to be used in the heightmap. The steps in the first sentence are my primary problem. I don't understand how the pixel positions correspond to positions on the sphere and what positions are sampled for the RMF to generate the pixels if only vertices cannot be used.

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  • Filling array with numbers from given range so that sum of adjacent numbers is square number

    - by REACHUS
    Problem: Fill all the cells using distinct numbers from <1,25 set, so that sum of two adjacent cells is a square number. (source: http://grymat.im.pwr.wroc.pl/etap1/zad1etp1213.pdf; numbers 20 and 13 have been given) I've already solved this problem analytically and now I would like to approach it using an algorithm. I would like to know how should I approach these kind of problems in general (not a solution, just a point for me to start).

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  • How do we keep dependent data structures up to date?

    - by Geo
    Suppose you have a parse tree, an abstract syntax tree, and a control flow graph, each one logically derived from the one before. In principle it is easy to construct each graph given the parse tree, but how can we manage the complexity of updating the graphs when the parse tree is modified? We know exactly how the tree has been modified, but how can the change be propagated to the other trees in a way that doesn't become difficult to manage? Naturally the dependent graph can be updated by simply reconstructing it from scratch every time the first graph changes, but then there would be no way of knowing the details of the changes in the dependent graph. I currently have four ways to attempt to solve this problem, but each one has difficulties. Nodes of the dependent tree each observe the relevant nodes of the original tree, updating themselves and the observer lists of original tree nodes as necessary. The conceptual complexity of this can become daunting. Each node of the original tree has a list of the dependent tree nodes that specifically depend upon it, and when the node changes it sets a flag on the dependent nodes to mark them as dirty, including the parents of the dependent nodes all the way down to the root. After each change we run an algorithm that is much like the algorithm for constructing the dependent graph from scratch, but it skips over any clean node and reconstructs each dirty node, keeping track of whether the reconstructed node is actually different from the dirty node. This can also get tricky. We can represent the logical connection between the original graph and the dependent graph as a data structure, like a list of constraints, perhaps designed using a declarative language. When the original graph changes we need only scan the list to discover which constraints are violated and how the dependent tree needs to change to correct the violation, all encoded as data. We can reconstruct the dependent graph from scratch as though there were no existing dependent graph, and then compare the existing graph and the new graph to discover how it has changed. I'm sure this is the easiest way because I know there are algorithms available for detecting differences, but they are all quite computationally expensive and in principle it seems unnecessary so I'm deliberately avoiding this option. What is the right way to deal with these sorts of problems? Surely there must be a design pattern that makes this whole thing almost easy. It would be nice to have a good solution for every problem of this general description. Does this class of problem have a name?

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  • NHibernate Tutorial #5 - Working with Many to Many relationships

    - by BobPalmer
    After a short break last week, I wanted to make sure I made time to publish the next in my series of tutorials on NHibernate. This week I'll be covering Many to Many relationships, the hilo algorithm, IdBag element, and touch on Lazy Loading. You can view the entire article at this link: http://docs.google.com/Doc?docid=0AUP-rKyyUMKhZGczejdxeHZfMjZkdjd3cjJnMg&hl=en As always, feedback and any technical bits I may have missed are always appreciated! -Bob Palmer

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  • When to skip solving the general problem and settling for the specific problem?

    - by Peter Smith
    I've been working hard on trying to develop a general solution to my problem, but I cannot seem to formulate a proper algorithm for it, at least one that doesn't take a ton of inaccurate grunt work building a lookup table. I have a solution already for the specific requirement, but it requires the software's configuration to be changed every time the software is loaded with a different geographic area's datasets. So is it better to be finished and move on for now, or to keep attempting to solve the general problem knowing that the specific problems will keep popping up?

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  • Fraud and Anomaly Detection using Oracle Data Mining YouTube-like Video

    - by chberger
    I've created and recorded another YouTube-like presentation and "live" demos of Oracle Advanced Analytics Option, this time focusing on Fraud and Anomaly Detection using Oracle Data Mining.  [Note:  It is a large MP4 file that will open and play in place.  The sound quality is weak so you may need to turn up the volume.] Data is your most valuable asset. It represents the entire history of your organization and its interactions with your customers.  Predictive analytics leverages data to discover patterns, relationships and to help you even make informed predictions.   Oracle Data Mining (ODM) automatically discovers relationships hidden in data.  Predictive models and insights discovered with ODM address business problems such as:  predicting customer behavior, detecting fraud, analyzing market baskets, profiling and loyalty.  Oracle Data Mining, part of the Oracle Advanced Analytics (OAA) Option to the Oracle Database EE, embeds 12 high performance data mining algorithms in the SQL kernel of the Oracle Database. This eliminates data movement, delivers scalability and maintains security.  But, how do you find these very important needles or possibly fraudulent transactions and huge haystacks of data? Oracle Data Mining’s 1 Class Support Vector Machine algorithm is specifically designed to identify rare or anomalous records.  Oracle Data Mining's 1-Class SVM anomaly detection algorithm trains on what it believes to be considered “normal” records, build a descriptive and predictive model which can then be used to flags records that, on a multi-dimensional basis, appear to not fit in--or be different.  Combined with clustering techniques to sort transactions into more homogeneous sub-populations for more focused anomaly detection analysis and Oracle Business Intelligence, Enterprise Applications and/or real-time environments to "deploy" fraud detection, Oracle Data Mining delivers a powerful advanced analytical platform for solving important problems.  With OAA/ODM you can find suspicious expense report submissions, flag non-compliant tax submissions, fight fraud in healthcare claims and save huge amounts of money in fraudulent claims  and abuse.   This presentation and several brief demos will show Oracle Data Mining's fraud and anomaly detection capabilities.  

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  • Programming Language, Turing Completeness and Turing Machine

    - by Amumu
    A programming language is said to be Turing Completeness if it can successfully simulate a universal TM. Let's take functional programming language for example. In functional programming, function has highest priority over anything. You can pass functions around like any primitives or objects. This is called first class function. In functional programming, your function does not produce side effect i.e. output strings onto screen, change the state of variables outside of its scope. Each function has a copy of its own objects if the objects are passed from the outside, and the copied objects are returned once the function finishes its job. Each function written purely in functional style is completely independent to anything outside of it. Thus, the complexity of the overall system is reduced. This is referred as referential transparency. In functional programming, each function can have its local variables kept its values even after the function exits. This is done by the garbage collector. The value can be reused the next time the function is called again. This is called memoization. A function usually should solve only one thing. It should model only one algorithm to answer a problem. Do you think that a function in a functional language with above properties simulate a Turing Machines? Functions (= algorithms = Turing Machines) are able to be passed around as input and returned as output. TM also accepts and simulate other TMs Memoization models the set of states of a Turing Machine. The memorized variables can be used to determine states of a TM (i.e. which lines to execute, what behavior should it take in a give state ...). Also, you can use memoization to simulate your internal tape storage. In language like C/C++, when a function exits, you lose all of its internal data (unless you store it elsewhere outside of its scope). The set of symbols are the set of all strings in a programming language, which is the higher level and human-readable version of machine code (opcode) Start state is the beginning of the function. However, with memoization, start state can be determined by memoization or if you want, switch/if-else statement in imperative programming language. But then, you can't Final accepting state when the function returns a value, or rejects if an exception happens. Thus, the function (= algorithm = TM) is decidable. Otherwise, it's undecidable. I'm not sure about this. What do you think? Is my thinking true on all of this? The reason I bring function in functional programming because I think it's closer to the idea of TM. What experience with other programming languages do you have which make you feel the idea of TM and the ideas of Computer Science in general? Can you specify how you think?

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  • SEO As the Online Business Traffic Driver

    The SEO means that the online business marketer can drive his site or blog to the top places at the search engine result pages with the selected keywords. This requires, that a marketer knows the search engine algorithm, i.e. according to which criteria the engine will put the sites in a certain order.

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  • Fuzzy-String Search: Find misspelled information with T-SQL

    An optimized Damerau-Levenshtein Distance (DLD) algorithm for "fuzzy" string matching in Transact-SQL 2000-2008 Learn Agile Database Development Best PracticesAgile database development experts Sebastian Meine and Dennis Lloyd are running day-long classes designed to complement Red Gate’s SQL in the City US tour. Classes will be held in San Francisco, Chicago, Boston and Seattle. Register Now.

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  • C# Algorithms for * Operator

    - by Harsha
    I was reading up on Algorithms and came across the Karatsuba multiplication algorithm and a little wiki-ing led to the Schonhage-Strassen and Furer algorithms for multiplication. I was wondering what algorithms are used on the * operator in C#? While multiplying a pair of integers or doubles, does it use a combination of algorithms with some kind of strategy based on the size of the numbers? How could I find out the implementation details for C#?

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  • Exalogic 2.0.1 Tea Break Snippets - Creating and using Distribution Groups

    - by The Old Toxophilist
    By default running your Exalogic in a Virtual provides you with, what to Cloud Users, is a single large resource and they can just create vServers and not care about how they are laid down on the the underlying infrastructure. All the Cloud Users will know is that they can create vServers. For example if we have a Quarter Rack (8 Nodes) and our Cloud User creates 8 vServers those 8 vServers may run on 8 distinct nodes or may all run on the same node. Although in many cases we, as Cloud Users, may not be to worried how the Virtualisation Algorithm decides where to place our vServers there are cases where it is extremely important that vServers run on distinct physical compute nodes. For example if we have a Weblogic Cluster we will want the Servers with in the cluster to run on distinct physical node to cover for the situation where one physical node is lost. To achieve this the Exalogic Virtualised implementation provides Distribution Groups that define and anti-aliasing policy that the underlying Virtualisation Algorithm will take into account when placing vServers. It should be noted that Distribution Groups must be created before you create vServers because a vServer can only be added to a Distribution Group at creation time. Creating A Distribution Group To create a Distribution Groups we will first need to select the Account in which we want the Distribution Group to be created. Once we have selected the account we will see the Interface update and Account specific Actions will be displayed within the Action Panes. From the Action pane (or Right-Click on the Account) select the "Create Distribution Group" action. This will initiate the create wizard as follows. Distribution Group Details Within the first Step of the Wizard we can specify the name of the distribution group and this should be unique. In addition we can provide a detailed description of the group. Distribution Group Configuration The second step of the configuration wizard allows you to specify the number of elements that are required within this group and will specify a maximum of the number of nodes within you Exalogic. At this point it is always better to specify a group with spare capacity allowing for future expansion. As vServers are added to group the available slots decrease. Summary Finally the last step of the wizard display a summary of the information entered.

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  • Parameterize Charts using Excel Slicers in PowerPivot

    - by Marco Russo (SQLBI)
    One new nice feature of Excel 2010 is the Slicer. Usually, slicers are used to filter data in a PivotTable. But they might be also useful to parameterize an algorithm or a chart! We discussed this technique in our book , but Alberto Ferrari wrote a post that shows how to use this technique to allow the user to select two stocks that should be compared in an Excel Chart – as you might imagine, this will work also when you will publish the workbook on SharePoint! This is the result: Nice to see that...(read more)

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  • Question about BoundingSpheres and Ray intersections

    - by NDraskovic
    I'm working on a XNA project (not really a game) and I'm having some trouble with picking algorithm. I have a few types of 3D models that I draw to the screen, and one of them is a switch. So I'm trying to make a picking algorithm that would enable the user to click on the switch and that would trigger some other function. The problem is that the BoundingSphere.Intersect() method always returns null as result. This is the code I'm using: In the declaration section: ` //Basic matrices private Matrix world = Matrix.CreateTranslation(new Vector3(0, 0, 0)); private Matrix view = Matrix.CreateLookAt(new Vector3(10, 10, 10), new Vector3(0, 0, 0), Vector3.UnitY); private Matrix projection = Matrix.CreatePerspectiveFieldOfView(MathHelper.ToRadians(45), 800f / 600f, 0.01f, 100f); //Collision detection variables Viewport mainViewport; List<BoundingSphere> spheres = new List<BoundingSphere>(); Ray ControlRay; Vector3 nearPoint, farPoint, nearPlane, farPlane, direction; ` And then in the Update method: ` nearPlane = new Vector3((float)Mouse.GetState().X, (float)Mouse.GetState().Y, 0.0f); farPlane = new Vector3((float)Mouse.GetState().X, (float)Mouse.GetState().Y, 10.0f); nearPoint = GraphicsDevice.Viewport.Unproject(nearPlane, projection, view, world); farPoint = GraphicsDevice.Viewport.Unproject(farPlane, projection, view, world); direction = farPoint - nearPoint; direction.Normalize(); ControlRay = new Ray(nearPoint, direction); if (spheres.Count != 0) { for (int i = 0; i < spheres.Count; i++) { if (spheres[i].Intersects(ControlRay) != null) { Window.Title = spheres[i].Center.ToString(); } else { Window.Title = "Empty"; } } ` The "spheres" list gets filled when the 3D object data gets loaded (I read it from a .txt file). For every object marked as switch (I use simple numbers to determine which object is to be drawn), a BoundingSphere is created (center is on the coordinates of the 3D object, and the diameter is always the same), and added to the list. The objects are drawn normally (and spheres.Count is not 0), I can see them on the screen, but the Window title always says "Empty" (of course this is just for testing purposes, I will add the real function when I get positive results) meaning that there is no intersection between the ControlRay and any of the bounding spheres. I think that my basic matrices (world, view and projection) are making some problems, but I cant figure out what. Please help.

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  • SSIS and Parallelism: The Unseen Minions

    Sometimes, a procedural database process cannot easily be reduced to a set-based algorithm in order to reduce the time it takes. Then, you have to find other ways to parallelise it. Other ways? Josef shows how to use SSIS to drastically reduce the time that such a process takes.

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  • Finding duplicate files?

    - by ub3rst4r
    I am going to be developing a program that detects duplicate files and I was wondering what the best/fastest method would be to do this? I am more interested in what the best hash algorithm would be to do this? For example, I was thinking of having it get the hash of each files contents and then group the hashes that are the same. Also, should there be a limit set for what the maximum file size can be or is there a hash that is suitable for large files?

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  • Finding the order of a set's elements

    - by Maciej Stachowski
    A little rephrased, in the form of a game, real-life problem: Suppose there is a set of elements {1, 2, ..., n}. Player A has chosen a single permutation of this set. Player B wants to find out the order of the elements by asking questions of form "Is X earlier in the permutation than Y?", where X and Y are elements of the set. Assuming B wants to minimize the amount of questions, how many times would he have to ask, and what would be the algorithm?

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  • What are known approaches to graphing algebraic expressions?

    - by jeremynealbrown
    I am planning to build an expression parser that will be used to graph algebraic functions ( think TI-83 ) with JavaScript. Functions will take the form of f(x)= Aside from typical operators such as: + - * / ^ I'd also like to add support for inline functions such as: sin(), cos(), log() and random(). I have looked at implementing the Shunting Yard algorithm for parsing expressions, but it does not look like an efficient approach to evaluating a function with a hundreds or thousands of inputs. What other known algorithms exist for this task?

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  • Java heap space

    - by java_mouse
    In Java/JVM, why do we call the memory place where Java creates objects as "Heap"? Does it use the Heap Data Structure to create/remove/maintain the objects? As I read in the documentation of Heap data structure, the algorithm compares the objects with existing nodes and places them in such a way that Parent object is "greater" than the children. ( Or "lesser" in case of min heap). So in JVM, how are the objects compared against each other before placing them in the heap?

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  • Pathfinding for fleeing

    - by Philipp
    As you know there are plenty of solutions when you wand to find the best path in a 2-dimensional environment which leads from point A to point B. But how do I calculate a path when an object is at point A, and wants to get away from point B, as fast and far as possible? A bit of background information: My game uses a 2d environment which isn't tile-based but has floating point accuracy. The movement is vector-based. The pathfinding is done by partitioning the game world into rectangles which are walkable or non-walkable and building a graph out of their corners. I already have pathfinding between points working by using Dijkstras algorithm. The use-case for the fleeing algorithm is that in certain situations, actors in my game should perceive another actor as a danger and flee from it. The trivial solution would be to just move the actor in a vector in the direction which is opposite from the threat until a "safe" distance was reached or the actor reaches a wall where it then covers in fear. The problem with this approach is that actors will be blocked by small obstacles they could easily get around. As long as moving along the wall wouldn't bring them closer to the threat they could do that, but it would look smarter when they would avoid obstacles in the first place: Another problem I see is with dead ends in the map geometry. In some situations a being must choose between a path which gets it faster away now but ends in a dead end where it would be trapped, or another path which would mean that it wouldn't get that far away from the danger at first (or even a bit closer) but on the other hand would have a much greater long-term reward in that it would eventually get them much further away. So the short-term reward of getting away fast must be somehow valued against the long-term reward of getting away far. There is also another rating problem for situations where an actor should accept to move closer to a minor threat to get away from a much larger threat. But completely ignoring all minor threats would be foolish, too (that's why the actor in this graphic goes out of its way to avoid the minor threat in the upper right area): Are there any standard solutions for this problem?

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  • SEO Tips

    SEO is the acronym for search engine optimization. The term "optimization" has been defined as a complete set of procedures that are implemented to make the system fully functional. In the case of search engine optimization, the websites are designed to match the algorithm of the search engines so that the "crawlers" can easily pick up the pages for indexing purposes.

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