Just Saying Hello! Come Check Out My Sounds

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Hi there, im new to this forum. Just wanted to say hello and tell you guys that I make a lot of different music in various styles. [wording deleted by moderator - use the Classifieds to seek work]


Edited by Tom Sloper

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    • By deltaKshatriya
      Hey all, 
      This isn't really a post that fits into any particular forum, so I'm posting it here, but feel free to move it mods, if you feel that it should move. I figured it isn't really specifically about game dev related careers.
      I'm a recent college grad, currently working as a software engineer as part of a rotational program, so I'll be spending some time in my current role then rotating to a new location and new software engineering related position. I did my undergrad in Computer Science, and while Computer Science had been my main career interest for quite some time before college, while working my way through college my main focus really was just to get done with the degree, get a job, and be done with the extreme stress/too much work during college. Now that I'm out, I'm not as sure about my career direction as I was before. While I do still do like Computer Science, software engineering, etc., my current position, although well paying, doesn't really involve me doing much on a day to day basis (for now at least though that's subject to change). The good news is that I've got a lot of control over where I rotate to next. Interestingly enough, initially I got interested in Computer Science because of game dev (as a teenager at least). Then that morphed into AI and machine learning. Now it's....unknown really.
      Now the thing is I've kind of been bouncing around in all sorts of directions. I absolutely love 3d art and have been actively trying to get better at it. I've also taken up writing and considered trying to write a novel in my spare time. Then I'm finding graphics programming very interesting as well (although that's not what my day job is), and I still have quite an interest in machine learning, data science, text mining, etc.
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    • By Levi Lohman
      First off, I have some experience in coding, and I've been told I am talented in the ways of mathematics, but I never learned an entire programming language well enough to make an actual game. But I'm not looking for a game engine where there is no coding or scripting at all, I would prefer something where you can set up the game world or levels by dragging and dropping objects in. But I could control the behavior of the objects through simple logic parameters that you set up by selecting things from lists and inputting data. 
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      Or if you were making an RPG and you wanted to define how a certain attack worked and had already set up variables for the stats of the player, enemies, and equipment you could type in some things like "preDamage = (weaponAtk x 1.25) x ((playerStrgth / 100) + 1)" and "enemyDefence = enemyArmor x ((enemyEnd / 100) + 1)" and "actualDamage = preDamage - enemyDefence" then you would select an if/then/else template saying something like "if actualDamage < 0, actualDamage = 0, else enemyHP = enemyHP - actualDamage"

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    • By deltaKshatriya
      Hey all,
      As some of you may know, I do have a Computer Science background, but either by chance/design/fate/insert stupid excuse here, I didn't take any graphics courses in my undergraduate degree, but now I'd be very interested in at least learning the basics of graphics and potentially pursuing more in graphics. I'm interested in all sorts of graphics in general, so everything from real-time engines to rendering engines like Arnold, Octane, etc. Can anyone point me in the right directions for books/tutorials?
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    • By nihitori
      Hello everyone!

      I'm one of the creators of the Colossal Game Music Collection and, as we now approach the end of the first year in which the collection has been released, we are currently planning our first major update to it...  As such, we thought it would be cool to ask you guys first about what sort of music content indie devs are most looking for and what they think it's currently missing on the asset markets. We would truly appreciate your opinions on this, as it would be crucial to improve the quality and usability of our collection. Here it goes:

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      - The second question is in regards to how the music itself is presented in the asset packs. For instance, we have been making 5 original tracks per pack available on the collection, available as both full tracks and seamless loops (sometimes with also smaller / longer versions available, as well as multiple small loops). Do you think this is the best approach? Or would you prefer the music to be presented in any other way?

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    • By
      This is an extract from Practical Game AI Programming from Packt. Click here to download the book for free!
      When humans play games – like chess, for example – they play differently every time. For a game developer this would be impossible to replicate. So, if writing an almost infinite number of possibilities isn’t a viable solution game developers have needed to think differently. That’s where AI comes in. But while AI might like a very new phenomenon in the wider public consciousness, it’s actually been part of the games industry for decades.
      Enemy AI in the 1970s
      Single-player games with AI enemies started to appear as early as the 1970s. Very quickly, many games were redefining the standards of what constitutes game AI. Some of those examples were released for arcade machines, such as Speed Race from Taito (a racing video game), or Qwak (a duck hunting game using a light gun), and Pursuit (an aircraft fighter) both from Atari. Other notable examples are the text-based games released for the first personal computers, such as Hunt the Wumpus and Star Trek, which also had AI enemies.
      What made those games so enjoyable was precisely that the AI enemies that didn't react like any others before them. This was because they had random elements mixed with the traditional stored patterns, creating games that felt unpredictable to play. However, that was only possible due to the incorporation of microprocessors that expanded the capabilities of a programmer at that time. Space Invaders brought the movement patterns and Galaxian improved and added more variety, making the AI even more complex. Pac-Man later on brought movement patterns to the maze genre – the AI design in Pac-Man was arguably as influential as the game itself.
      After that, Karate Champ introduced the first AI fighting character and Dragon Quest introduced the tactical system for the RPG genre. Over the years, the list of games that has used artificial intelligence to create unique game concepts has expanded. All of that has essentially come from a single question, how can we make a computer capable of beating a human in a game?
      All of the games mentioned used the same method for the AI called finite-state machine (FSM). Here, the programmer inputs all the behaviors that are necessary for the computer to challenge the player. The programmer defined exactly how the computer should behave on different occasions in order to move, avoid, attack, or perform any other behavior to challenge the player, and that method is used even in the latest big budget games.
      From simple to smart and human-like AI
      One of the greatest challenges when it comes to building intelligence into games is adapting the AI movement and behavior in relation to what the player is currently doing, or will do. This can become very complex if the programmer wants to extend the possibilities of the AI decisions.
      It's a huge task for the programmer because it's necessary to determine what the player can do and how the AI will react to each action of the player. That takes a lot of CPU power. To overcome that problem, programmers began to mix possibility maps with probabilities and perform other techniques that let the AI decide for itself how it should react according to the player's actions. These factors are important to be considered while developing an AI that elevates a games’ quality.
      Games continued to evolve and players became even more demanding. To deliver games that met player expectations, programmers had to write more states for each character, creating new in-game and more engaging enemies.
      Metal Gear Solid and the evolution of game AI
      You can start to see now how technological developments are closely connected to the development of new game genres. A great example is Metal Gear Solid; by implementing stealth elements, it moved beyond the traditional shooting genre. Of course, those elements couldn't be fully explored as Hideo Kojima probably intended because of the hardware limitations at the time. However, jumping forward from the third to the fifth generation of consoles, Konami and Hideo Kojima presented the same title, only with much greater complexity. Once the necessary computing power was there, the stage was set for Metal Gear Solid to redefine modern gaming.
      Visual and audio awareness
      One of the most important but often underrated elements in the development of Metal Gear Solid was the use of visual and audio awareness for the enemy AI. It was ultimately this feature that established the genre we know today as a stealth game. Yes, the game uses Path Finding and a FSM, features already established in the industry, but to create something new the developers took advantage of some of the most cutting-edge technological innovations. Of course the influence of these features today expands into a range of genres from sports to racing.
      After that huge step for game design, developers still faced other problems. Or, more specifically, these new possibilities brought even more problems. The AI still didn't react as a real person, and many other elements were required, to make the game feel more realistic.
      Sports games
      This is particularly true when we talk about sports games. After all, interaction with the player is not the only thing that we need to care about; most sports involve multiple players, all of whom need to be ‘realistic’ for a sports game to work well.
      With this problem in mind, developers started to improve the individual behaviors of each character, not only for the AI that was playing against the player but also for the AI that was playing alongside them. Once again, Finite State Machines made up a crucial part of Artificial Intelligence, but the decisive element that helped to cultivate greater realism in the sports genre was anticipation and awareness. The computer needed to calculate, for example, what the player was doing, where the ball was going, all while making the ‘team’ work together with some semblance of tactical alignment. By combining the new features used in the stealth games with a vast number of characters on the same screen, it was possible to develop a significant level of realism in sports games. This is a good example of how the same technologies allow for development across very different types of games.
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      A final useful example of how game realism depends on great AI is F.E.A.R., developed by Monolith Productions. What made this game so special in terms of Artificial Intelligence was the dialog between enemy characters. While this wasn’t strictly a technological improvement, it was something that helped to showcase all of the development work that was built into the characters' AI. This is crucial because if the AI doesn't say it, it didn't happen.
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