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1  Games Center / WIP games, tools & toy projects / Re: Generated Graph optimized A* Pathfinding on: 2017-12-16 07:37:40
Hmm.. precomputed flow maps seem like they would only work with static endpoints, as they would be function of the destination/exit endpoint. I wonder what your use case was, why would a map have multiple static entrances / exits,  but not a precomputed path to follow?
This was for fairly complex areas and the flow maps also solved the beginning and ending of the paths. Pre-computed paths should do much the same thing.

In my case it was actually hexagonal tiles with no corridors. The shared entrance/exits were the 12 points at vertices and centre of each edge of the tiles.
2  Games Center / WIP games, tools & toy projects / Re: Generated Graph optimized A* Pathfinding on: 2017-12-15 21:11:03
@Jono is very knowledgeable on this topic, he's actually taught A* and other algorithms in class. He provided some good tips for me here:
And I'm still lurking here! Not a lot to add though as this all looks pretty slick to me.

I've implemented a similar style of map pathing between entrance/exit nodes of map areas taken from a fixed set (this would be analogous to having a fixed set of room layouts in these maps). The areas had additional static obstacles inside them and I pregenerated flow fields towards each exit for every room. The flow fields might work around movement problems with non-rectangular rooms too I suppose.
3  Game Development / Shared Code / Re: "Better" LinkedList implementation on: 2017-06-27 15:01:18
Interesting, it'd be cool to see a.comparison between that and my implementation.

To make it comparable it has to be turned into a doubly-linked list and be generalised to hold objects instead of just ints.

I tried this out, using elements with a "getID" method to enable the random access. It loses the cache coherency from storing data+references in one array, as well as having more overhead from the extra book-keeping of the previous links. In the end approximately 500x faster than java.util.LinkedList on the random access operations but roughly the same on the removeFirsts -- there is a lot of variance between tests on this though.

In short, no good reason to move from your implementation. It moves the next/prev links out of the elements and into the single pool class, but at the cost of some efficiency.
4  Game Development / Shared Code / Re: "Better" LinkedList implementation on: 2017-06-21 10:00:17
A long time ago I did a linked list pool (but only for int values).

This was much quicker than object-based linked lists, though I was using it for multiple lists that were often merged/appended. That's a bit different from the use-case here.
5  Discussions / Miscellaneous Topics / Re: What I did today on: 2017-05-10 11:54:33
Seems like a simple enough challenge Smiley
void reverse(float[] array){
    for(int i = 0; i<array.length/2; i++){
        float cache = array[i];
        array[i] = array[array.length-1-i];
        array[array.length-1-i] = cache;

How'd I do?

While Riven was joking (or at least poking fun at how pathetic most industry interviews are) I do have some advice.

You'll find that if the company is any any good at all, for the first simple warm-up questions you will impress them more with succinct answers. Know a relevant method in the API, a quick shortcut etc. It doesn't need to be optimised, just so long as it's reasonable big-O.

I would first ask if Python was ok, then give

6  Discussions / Miscellaneous Topics / Re: What's in your gamedev software rig ? on: 2017-01-24 22:07:55
A10-7850K at 45W (no fan)
2 64GB SSD and 4TB on NAS.

Ubuntu 16.10
Eclipse with Java 8 and vi plugin

The last one in bold because you should all try it out. It's Inkle's editor for Ink interactive stories.
7  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2017-01-03 20:01:19
It's reproducable but definitely a bug of some sort. It plays fast after f6-i6 because it can see that state is a certain win for white. For some reason during the search, even with no pruning, it fails to see that this is a winning move for white.

I'll get the source code released first then see if I can find time to sort this out. Will keep you posted. Smiley
8  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2017-01-03 17:53:09
Oh. It does that when it can see the end of the game without search. It is deterministic so I'll should be able to recreate that game. Shame it failed to play prpperly on the day...
9  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2017-01-03 15:19:21
Wow, just saw the one where J.A.R.L. was attacking. Looks like it seriously broke, I'm not sure it should ever choose those last couple of moves even if it is given almost no time to think. I guess the pruning somehow blew up or something.
10  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2017-01-02 19:33:45
I'd love to see the game records if you could make them available. Any comments on the games would be nice too since I don't play well and so don't pick up on a lot of the nuance (both good and bsd) in the moves.
11  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2016-12-13 16:15:57
Cool, good to hear. Right now I'm pretty sure it is hard-coded to use 10s regardless of how much time it is told it has, so it won't get any better than that Smiley

12  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2016-12-13 14:02:10
Righto, done via dropbox. Let me know if you don't get a message from dropbox (or have any issues running the AI).
13  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2016-12-12 13:00:42
I'm having some trouble submitting by email -- gmail blocks runnable jars in attachments. Any ideas on how to get around this?
14  Discussions / Miscellaneous Topics / Re: What I did today on: 2016-10-26 07:53:48
Started work on a logic engine for use in (my) games. I got the main design done and unification working.

Parser p = new Parser();
Term f1 = p.parseTerm("foo(X,b)");
Term f2 = p.parseTerm("foo(a,Y)");


and Prolog-style lists:
Term t1 = p.parseTerm("[Y,b,c]");
Term t2 = p.parseTerm("[a|[X|[c|[]]]]");


Next up are knowledge bases, rules and backtracking.
15  Game Development / Newbie & Debugging Questions / Re: Spotlights and decorator on: 2016-09-14 20:40:33
It feels a bit mixed up.

I don't think the subclass RotatingSpotLight should exist. This is a behaviour and so everything can be put in a "RotatingLightDelegate" that could be assigned an angle on construction.

The RotatingLightDelegate would replace the RotatingSplotLightDelegate -- which is misnamed anyway as it can apply to any light, not just splot lights.

RotatingSplotLightDelegate is probably more accurately named "MoveOnRenderDelegate". As an aside, updating on render is a bad idea (but not really relevant to the design pattern discussion).

The core idea that's missing is that any delegate can wrap any light (including other delegates). If you ever start making code that relies on specific pairs of delegates/lights being used then the design has gone wrong.
16  Java Game APIs & Engines / OpenGL Development / Re: *AMD testing needed!* Vertex cache shenanigans on: 2016-09-12 20:16:43
Some errors but seemed to run on an AMD APU

Vertex shader log:
0:1(10): error: GLSL 3.30 is not supported. Supported versions are: 1.10, 1.20, 1.30, 1.00 ES, and 3.00 ES

Fragment shader log:
0:1(10): error: GLSL 3.30 is not supported. Supported versions are: 1.10, 1.20, 1.30, 1.00 ES, and 3.00 ES

Link log:
error: linking with uncompiled shadererror: linking with uncompiled shader
Batch size test invocations: 8129 / 3145728
Calculated vertex cache batch size: 387

Cache size 1 invocation test: 8129 / 3145728
Cache size 2 invocation test: 16258 / 3145728
Cache size 3 invocation test: 24387 / 3145728
Cache size 4 invocation test: 32516 / 3145728
Cache size 5 invocation test: 40645 / 3145728
Cache size 6 invocation test: 48774 / 3145728
Cache size 7 invocation test: 56903 / 3145728
Cache size 8 invocation test: 65032 / 3145728
Cache size 9 invocation test: 73161 / 3145728
Cache size 10 invocation test: 81290 / 3145728
Cache size 11 invocation test: 89419 / 3145728
Cache size 12 invocation test: 97548 / 3145728
Cache size 13 invocation test: 105677 / 3145728
Cache size 14 invocation test: 113806 / 3145728
Cache size 15 invocation test: 398303 / 3145728
Cache size 16 invocation test: 699062 / 3145728
Cache size 17 invocation test: 3145728 / 3145728

  Renderer: Gallium 0.4 on AMD KAVERI (DRM 2.43.0, LLVM 3.8.0)
  Calculated vertex cache batch size: 387
  Cache size: 16

17  Discussions / Miscellaneous Topics / Re: What I did today on: 2016-09-05 08:33:08
It's very realistic. Olaf Ragnarson lives there and he's one scary dude with a big axe. It's safest to take the scenic route.

A simple brute-force way would be to run the path generation several times and then pick the result with the least number of paths. Another way would be to prune paths with connections to mandatory roads last.

If I calculate the total distance to a point in the graph, I can then add paths back in and see what addition lowers the total distance most.

But hey, the Vangardians don't even walk on the paths yet Smiley
You're looking for something between a Shortest Path Tree (efficient movement) and a Minimum Spanning Tree (least road construction).

If your villages are small enough for a quadratic algorithm then I'd do:
- for every pair of locations
  - add the shortest path between them, where existing paths cost 0.1 and non-paths cost 1.0
18  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2016-08-18 08:54:09
Eeeeeeeeek! My entry will serve the purpose of making everyone (else) a winner Sad

The fellow who runs whipped up a bot in a day or two which is reliably better than OpenTafl, so I'll be right there with you at the back of the pack.
Also, your AI might just end up being the kryptonite to someone else's. Right now my AI looks like it makes smart moves, but if you just aggressively capture pieces it really starts to fall apart.
19  Games Center / WIP games, tools & toy projects / Re: OpenTafl: old terminal graphics meet Old Norse board games on: 2016-07-27 08:36:54
Could you explain the AI that goes behind this? The class structure and methods, really. How are you going about this?
That would be quite a long explanation.. but in brief, the important classes:
  • Board: maintains game state (positions of pieces) using minimal memory. Provides useful functions that make some assumptions about rules, e.g.: get all open spaces vertically and horizontally from a given piece, or from all pieces of a certain colour. Also whether the simple win conditions have been met -- white in a corner or king captured.
  • "Heavy" Board: a sub-class of Board that adds more information that can be inferred from the game state. E.g. counts of pieces, whether white is surrounded, which pieces are threatened (can be captured in one turn) etc. Ideally the extra information should be able to me modified incrementally when a piece is moved.
  • Transition/HeavyTransition: classes that can apply moves to a Board and can undo moves.
  • Evaluator: An interface that provides a function for evaluating who is winning in a given Board position. The simplest one says 0 when black has won, 1 when white has won, and 0.5 otherwise. This is where heuristics can be implemented.
  • Search: Interface that takes an initial board state, an Evaluator, a Transition factory (that produces valid transitions for a given Board), and returns the move that produces the best looking Board. I have two implementations:
    • IDDFS (iterative deepening depth-first search) using min/max with alpha/beta pruning. As this is depth-first, adding and undoing moves as it goes, memory is no issue. You can leave this running for days to evaluate positions if you want so is good for testing the correctness of other search strategies.
    • MCTS (Monte-Carlo tree search). This can be much better than IDDFS if you can get good playouts. This requires selecting fairly reasonable moves from any board position. Without lots of examples or good knowledge of the game this is pretty hard so I decided to shelve this strategy.

There are other bits that get added to improve things. For example, visited sets so you can reuse values when you encounter the same state multiple times. A function for classifying moves as interesting/unintersting that can be used either for MCTS playouts or for ordering the search in IDDFS. Plus plenty of heuristics that appear as concrete evaluators.

The light-weight states almost always lose out to heavy-weight states coupled with computationally expensive heuristics. Basically you should always do more work and search less. That seems to hold for Tafl, at least for me.

On my anemic PC I get 400k nodes per second searched using a vanilla board, and about 30k/second with heavy boards and heuristics. The slower search absolutely clobbers the faster one in games. It only gives up about 1 or 2 depth but has far better evaluation of position.
20  Games Center / WIP games, tools & toy projects / Re: OpenTafl: old terminal graphics meet Old Norse board games on: 2016-07-25 07:31:57
My AI has soaked up more time than I expected. It's playing ok, but I don't think it's anywhere near human level yet. At least it's at the point where all I have left to do is the fine tuning, so it'll definitely be playing in December Smiley
21  Discussions / General Discussions / Re: What does your dream language look like? on: 2016-07-08 07:38:38
I guess I'd start with Java but somehow shoehorn in some new features.
As in Python, nice syntax for:
  • generators, yield
  • list comprehensions
  • multiple return values
Other features:
  • const (for method parameters)
  • Duck typing for interfaces, checked at compile-time like Go
22  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2016-05-31 14:05:40
I've encountered a bug with the latest build (one after 0.2.5b). When playing with human (attackers) vs AI (defenders) the board state send with opponent-move commands stops including the king after the first capture.


move /4tttt3/5t5/3t7/t4T4t/t3TTT3t/tt1TTKTT1tt/t1T3T3t/t4T4t/4Tt5/11/3ttttt3/
opponent-move d11-d9 /4tttt3/5t5/3t7/t4T4t/t3TTT3t/tt1TT1TT1tt/t1T3T3t/t4T4t/3t1t5/11/4tttt3/

The opponent-move captured a piece at d10 (not the king), but the king still disappeared from the next board state.
23  Games Center / Contests / Re: The OpenTafl Computer Tafl Open - An Abstract Strategy AI Tournament on: 2016-05-16 11:28:23
I think I'll probably enter this. Thanks for the early heads-up, free time is hard to come by but I ought to be able to find a few days before December Smiley
24  Game Development / Artificial Intelligence / Re: Hidden Markov Models, how to train using Baum-Welch? on: 2015-10-19 19:45:36
The entire problem is taking in a stream of emissions/observations and predicting the next emission. The underlying states are irrelevant.

You mean it's irrelevant to your post because they've given you a structure? Out of interest, how many states are there and how many transitions with non-zero probability? If it's up to you to make the structure then this is a pretty critical step.

Baum-Welch seems to suck. If I repeatedly train my HMM with the entire sequence of emissions/observations, it eventually explodes into a HMM filled with 0s. The scarce information I've found says that this is due to overfitting.

I don't think that should be possible. The transition probabilities out of each state have to sum to 1, though that is including the "stay" transition back in to the state itself. Overfitting can generate some states with only a single non-zero probability transition in and out but you'll either need to have tons of states or be training it on the same sequence again and again.

What is the optimal way of training an HMM given a stream of data?

Baum-Welch is pretty good. I'd stick with that until you get it to work.

Given the sequence of emissions [a, b, c], to calculate the probability of each possible next emission I compute the probability of the emission [a, b, c] occurring given the current HMM state and then the probabilities of [a, b, c, <X>] occurring, where X is each possible emission. The conditional probability of each emission is then
p([a, b, c, <X>]) / p([a, b, c])
Is this the correct way of calculating the probability of the next emission?

After seeing [a,b,c] you could be in any of your states. Call the set of states <N>. You first need to calculate the probability of being in each n in <N>: P([a,b,c,n]). This is the "forward" step that you'll find documented (Wikipedia is fine for this).

In each of the states there will also be a probability of emitting each x in <X>: P(x|n). That's straight from the current model parameters.

For an emission x, P([a,b,c,x]) is the sum of all the ways x could be emitted, i.e. sum of P([a,b,c,n])*P(x|n).

If you follow through with the method above to just predict the next state I think you'll be doing Forward/Backward. If all you want is the single most likely state then it's much simpler to do Viterbi, which is just plain old dynamic programming applied to the HMM (and for me at least, is easier to understand).
25  Discussions / General Discussions / Re: What projects are you guys working on? How's progress going? on: 2015-07-01 12:09:05
Automatic interactive story generator. You give it a world and it makes a story that a user can branch at any point.

 Progress is.. progressing. As it has for the last 4 years or so. I hope to have an interactive text version for ~2 minute long stories working by the end of the year.
26  Discussions / Miscellaneous Topics / Re: advanced 'Knapsack problem' on: 2015-04-22 12:46:33
This also sounds like something you could potentially solve with a theorem prover like Z3.

Yeah, this is an SMT problem What you are doing is called constraint programming.

If you really want to roll your own, I'd do it this way:
- first make a solver that finds a solution to the hard (boolean) constraints
- generate a single valid solution
- traverse the space of valid solutions, testing the overall value of the soft constraints as you go
- after some time or after exhausting the search space, return the best result found so far

From your description of the problem it shouldn't be too hard to define a function that takes a valid solution and generates similar, valid solutions for the traversal, so this kind of approach should be ok.

If you can make the first step non-deterministic then keep repeating with greedy searches from new valid start points -- this is much less prone to getting stuck in local optima than evolutionary algorithms and will be quicker too.
27  Game Development / Shared Code / Re: Curve fitting on: 2015-04-01 16:08:27
I find the easiest way to understand the DFT is as least squares:

You're finding the best coefficients for a set of sinusoids so their sum is closest to your data. By using sufficient sinusoids of different frequencies these form a basis for all 1D signals, so you can get a perfect answer.

The X in that page are all the sinusoids as a matrix (one per column).
beta are the coefficients -- they're complex so you get magnitude and phase.
y is the data (your 1D signal).
28  Discussions / Miscellaneous Topics / Re: What I did today on: 2015-03-01 12:56:13
38.3 in average.

(1.0-0.001)^999 = 0.368063488

999 adjacent pairs, with each second item having a 1/1000 chance of matching the prior. Sorry, couldn't hold back.
29  Game Development / Game Play & Game Design / Re: Game to visit all squares without overlapping -- Squarenigma on: 2015-02-24 20:42:23
What the player is doing in that is making a Hamiltonian path in the grid, with fixed start and end points.

That can help a search find things like this: which is pretty close. A similar old game (from 1857):
30  Discussions / Miscellaneous Topics / Re: What I did today on: 2015-02-16 22:26:51
I finally have a solid initial implementation of a Goal planning system. It allows for entities to have goals and subgoals and to replan as circumstances change. A lot of GOAP material available is fiarly complicated from an implementation side, and it took a while for me to get to a simpler system that meets my needs.

I worked on a planning system too, but mine's overly complicated.

Today I fixed some bugs exposed by the fall-in-love and decide-sexuality actions.
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Java Gaming Resources
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2017-12-05 19:38:37

Java Gaming Resources
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Java Gaming Resources
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Java Gaming Resources
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List of Learning Resources
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List of Learning Resources
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SF/X Libraries
by philfrei
2017-03-02 08:45:19

SF/X Libraries
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