• Announcements

    • khawk

      Download the Game Design and Indie Game Marketing Freebook   07/19/17

      GameDev.net and CRC Press have teamed up to bring a free ebook of content curated from top titles published by CRC Press. The freebook, Practices of Game Design & Indie Game Marketing, includes chapters from The Art of Game Design: A Book of Lenses, A Practical Guide to Indie Game Marketing, and An Architectural Approach to Level Design. The GameDev.net FreeBook is relevant to game designers, developers, and those interested in learning more about the challenges in game development. We know game development can be a tough discipline and business, so we picked several chapters from CRC Press titles that we thought would be of interest to you, the GameDev.net audience, in your journey to design, develop, and market your next game. The free ebook is available through CRC Press by clicking here. The Curated Books The Art of Game Design: A Book of Lenses, Second Edition, by Jesse Schell Presents 100+ sets of questions, or different lenses, for viewing a game’s design, encompassing diverse fields such as psychology, architecture, music, film, software engineering, theme park design, mathematics, anthropology, and more. Written by one of the world's top game designers, this book describes the deepest and most fundamental principles of game design, demonstrating how tactics used in board, card, and athletic games also work in video games. It provides practical instruction on creating world-class games that will be played again and again. View it here. A Practical Guide to Indie Game Marketing, by Joel Dreskin Marketing is an essential but too frequently overlooked or minimized component of the release plan for indie games. A Practical Guide to Indie Game Marketing provides you with the tools needed to build visibility and sell your indie games. With special focus on those developers with small budgets and limited staff and resources, this book is packed with tangible recommendations and techniques that you can put to use immediately. As a seasoned professional of the indie game arena, author Joel Dreskin gives you insight into practical, real-world experiences of marketing numerous successful games and also provides stories of the failures. View it here. An Architectural Approach to Level Design This is one of the first books to integrate architectural and spatial design theory with the field of level design. The book presents architectural techniques and theories for level designers to use in their own work. It connects architecture and level design in different ways that address the practical elements of how designers construct space and the experiential elements of how and why humans interact with this space. Throughout the text, readers learn skills for spatial layout, evoking emotion through gamespaces, and creating better levels through architectural theory. View it here. Learn more and download the ebook by clicking here. Did you know? GameDev.net and CRC Press also recently teamed up to bring GDNet+ Members up to a 20% discount on all CRC Press books. Learn more about this and other benefits here.

badday

Members
  • Content count

    22
  • Joined

  • Last visited

Community Reputation

100 Neutral

About badday

  • Rank
    Member
  1. You mean combining the potentialfields/layers using GPU (OpenCL, as we need to run it on our server, too)? Are there any code-snippets available which show something similar in action? Apart from that, our A*-algorithm should be optimized I think, so maybe someone might have a look at the code ( http://sourceforge.net/p/potentialfield/code/ci/b9930a37bc114a64601d976d0c2d774fa919789d/tree/ ) who is familiar with the algorithm. Thanks a lot.
  2. [quote]For example, we used potential fields to get units onto the road network, and they would then drive the road network (which is modelled as a graph) until they get close to their destination, at which point they get off the road again.[/quote] Hm... Our terrain is generated with some deterministic noise-generator, therefore a modelled graph would have to be computed, I'm not sure whether this is easy to archieve. [quote] It's *possible* to get the field systems to (say) find the bridge over the river, but it's not as good a solution as a better macro scale system. [/quote] I agree with you for that point, but our game has no such "high interest" places, so the only thing which might be a problem are more or less little obstacles (buildings or units), but not such things like rivers which influence to hole navigation-process much more.
  3. Our current implementation should make it quite unlikely (at least if we do not have really many or big obstacles) that a recalculation is necessary. Although, I'm not yet sure what you mean with the connection of times of recalculation and getting stuck, as any recalculation from some position does not differ from an initial calculation of the path from that position in our implementation. Maybe I understood you wrong. When it comes to what you say, that due to the dynamic layer, we need to go right or left, a problem which could - dependent on the implementation - occur is that we are dead-locked and have a force of 0. But I think you can avoid that if you have a different weight of the layers, which might come close to what you said to the second problem. So we might have some smooth gradient-potential around an unit up to a certain distance and than immediately an infinite value to avoid at any price that we collidate. That would - as far as I can see - avoid that we get dead-locked. We could also have some fallback, so if we really face a 0-force and are not at our target, let's clean the dynamic layer of any potentials for smooth moving (any gradients) and let's have only 0 or infinite values. I think it is very unlikely that the 0-force remains in this case, although I'm not yet sure. Thanks a lot for your help
  4. I think you talk about the "local optima problem" described here: [url="http://aigamedev.com/open/tutorials/potential-fields/#WhatabouttheLocalOptimaProblem"]http://aigamedev.com/open/tutorials/potential-fields/#WhatabouttheLocalOptimaProblem[/url] , don't you? What is talked about in this article is some problem resulting from an approach which doesn't rely on a path calculated with A*-star, so I think we can almost be sure that we won't have such a problem on the static-layer. Another point is the one you mentioned. This is a problem in fact, but I'm not sure whether this is a potential-field-approach problem. To solve this we might say to use some hybrid-approach (as you said, pure potential field approach seems not to be the best solution), e. g. using some fuzzy-logic-system to determine which potential to put around an object (while one object has only on potential) and therefore making sure that by combining various potentials without looking at the global context such a problem does not occur. So at the end, the AI is transformed to potentialfields and not the other way around.
  5. Hi there, we are currently developing an RTS-game and working on the fight-implementation. Of course you come to the field of AI immediately, so we thought how to realise the AI implementation. We looked for a straightforward technic and finally chose the potential(field)-approach. Let me point out what this means: All moving depends on potentials. So if you want to move some unit from A to B, we have a layer for the static world, that is the heightmap. So you make a regular A-star algorithm execution which is a bit different to what you use normally. We start at the target and go from there to find our start-position. The class path_potential_admin supplies the static layer, so obstacles are not considered. It also has some caching-functionality, so if this path is already known (specified by pos A and B), we can save time and supply our previously found path. This is possible as the static world never changes. The dynamic world is also based on potentials, that is e. g. a repulsive one for units or buildings so that we do not collide. We offer a few different potentials, just have a look at the code ( [url]http://sourceforge.net/p/potentialfield/code/ci/b9930a37bc114a64601d976d0c2d774fa919789d/tree/[/url] - it comes with a VS-project which is ready to compile and will create some pictures which illustrate how it works - be aware, might take a long time to finish). When it comes to the moving process, we need some force which tells us where to go. You can imagine that like a 3D-potential-field and some bullet. The bullet will always move downwards (due to the earth's gravitational pull). Downwards means the lowest potential in this context. So far to the theoretical idea and method, now we come to the real world and the problems we currently face with our implementation. We have some requirements: * do not rely on external libraries * be as performant as possible So we would like to discuss the following questions: * What do you think about this idea at all? * What improvements do you see in the implementation? * We are working with a hex-grid currently, what do you think about this approach? * There is an issue when it comes to mapping a quadratic heightmap to a hex-grid (you know radius of the inner circle and the side length are not equivalent, just see [url]http://upload.wikimedia.org/wikipedia/commons/e/e2/Sechseck-Zeichnung.svg[/url] ). This is a known issue and will be fixed soon * The A-star implementation is somehow not really efficient when it comes to a changed start-position. Are there any improvements? * Anything else you want to say. Thanks a lot for your contributions. Greetings, badday