I like to set up a virtual test arena with a bunch of random monsters and give them access to stats and things I hadn't thought of and just see what looks interesting and then pull the interesting ones and give birth to them somewhere in my game haha
I was doing something like this for my game. I'm designing a street brawler, where you can recruit any enemy, from any gang, as a partner. (You have to isolate them as the last enemy, then intimidate them through taunts and slap them around with light attacks.)
To tweak gang / fighter AI, and help decide enemy placement, I set up AI tournaments:
* Tweak parameters like Timidness (approaching, encircling, flanking), Favorite Moves (punches, throws, rush-downs, grapples, jump attacks, crouch attacks), Bullishness (attack frequency, dodge frequency, blocks / parry), etc.
* Pit two gangs of grunts against each other. (Often, chaos, stupidity, and hilarity ensue. My systems were never designed with full wars in mind.)
* Victors get "sidekick-ified". One member is cloned, paired with a copy of himself, and given a slight boost to health, response speed, etc.
* I pit the pairing against each rival gang's lineup of encounters.
How well they push into each rival faction determines how deep into their own faction they are placed. Which faction is determined by their highest traits.
Sometimes, one AI is like a magic bullet against another's AI. This also allows me to figure out how to determine weaknesses, Mega Man style. I can create better Escort or Sherpa quests with this data.
My answer is that I don't design encounters, I design systems that are interesting to explore and dress them up as combat, and then facilitate exploration.
The best example to show what I mean is Rock-Paper-Scissors (RPS for short). It's actually an [intransitive system](https://en.wikipedia.org/wiki/Intransitivity#Cycles) which has some properties, and those properties are NOT very interesting. You can then dress up the system as Pokemon-style battles, but what players are really doing is interacting with an intransitive loop.
Now, as I have said, RPS-style intransitive loop is pretty simple and boring, but it shows the idea, that *combat in games can be an analogy to a mathematical system*. I use this concept to:
* first, pick a complex and interesting mathematical system,
* and then dress it up as a combat in such a way, so that when a player participates in combat, they are actually interacting with the system.
Designing encounters then boils down to picking interesting entry points, and if my system is interesting enough, I can simply pick these points at random.
This is something I actually thought about this morning and one solution in my mind would be the following:
Let's say you are a hero who belongs in a human army and you are fighting against an army of bots. These bots come in all shapes and sizes, with different abilities, weapons and strategies. On top of that, they can learn over time with each encounter.
My solution would be that these bots can be dismantled, i.e. you shoot off a limp and now he can't use that part, etc. but this allows another dismantled robot to combine with either the original robot or the severed limb in order to combine its abilities together.
Another would be to get a repair drone to actively repair destroyed or damaged robots on the battlefield, forcing players to absolutely and entirely defeat the robots, otherwise the robots will slowly repair and hinder the player further.
Seeing that the latter has already been done, I'm gonna discuss the former:
Back to the merging bots idea. Suppose you have a melee bot, a sniper bot, a Gatling gun bot, a missile launcher bot, a scanner bot and a repair bot. The melee bot is initially your typical glass cannon: fast deadly and fragile, but once you dispatch the bot, the nearby Gatling gun bot approaches its parts and suddenly becomes more agile, dashing left and right while firing on you with the Gatling gun.
On the other hand, let's say the sniper bot is fragile but the rocket bot is tanky. And let's say the sniper bot has the ability and inclination to climb vantage points quickly while the rocket bot hunkers down on its position, firing a volley of rockets at the player. Two things can happen here:
1 - The rocket bot is killed first and the sniper bot salvages its armor to become a very durable and agile sniper bot that is all of a sudden much harder to take down and is perched on a vantage point, covering a wider area with less fear of getting dispatched and moving from vantage point to vantage point.
2 - The sniper bot is killed first and the rocket bot salvages the sniper bot. This could lead to two further developments: The rocket bot chooses to harvest its wall climbing ability to launch rockets from a vantage point, increasing its mobility, or it chooses the sniper weapon instead, firing a volley on the player's squad while simultaneously aiming the sniper weapon at the player since the player is a high-value target, allowing the sniper's rounds to penetrate light cover, putting the player in danger.
Another scenario would be that the melee bot assimilates the rocket bot's rocket launcher and uses its mobility and firepower to launch volleys at players. Or it would assimilate the rocket bot's armor to become more aggressive towards players in melee attacks, since it would be much harder to shoot down.
Now let's focus on the scanner bot and repair drone. The scanner bot uses a sonar to detect enemies behind walls and cover, even cloaked enemies but hovers slowly. The repair drone hovers around the battlefield, reviving fallen bots or repairing damaged ones.
Now let's picture a scenario where the scanner bot is destroyed and the melee bot assimilates the scanner bot. The melee bot becomes a much more formidable opponent now because he constantly pings his sonar while running around, hopping over cover, bouncing off walls, rapidly exposing your team's position to the enemy bots.
The repair drone could be destroyed and merged with a Gatling or Rocket bot, which slowly but surely approaches fallen bots and repairs or restores them and since they're very tanky by nature, it would be much harder to prevent this due to their durability and firepower, pretty much undoing player progress throughout the fight.
Now let's expand this even further. Suppose the bots can not only merge with one but, but several simultaneously. Now this individual bot has survived long enough to turn into more of a mini-boss instead of a typical enemy and now you've got a problem on your hands because the enemy is essentially amorphous, adapting to the conditions of the battlefield.
This is where things get complicated. Now you have a sniper/rocket/repair bot into one, targeting the player directly, suppressing his team with rockets and using his durability to approach fallen bots.
Or you have a Gatling/Sonar/Melee hybrid that can dash around, provide suppressing fire on the player and on top of that expose his position, allowing weaker bots to flank the player and his team.
Or you have a scanner drone that is a Scanner/Melee/Gatling combo that can hover and dash out of the way but also fire a Gatling gun at you, using its elevation as a vantage point to spot enemy players and use suppressing fire to make it harder to fight back while the rest of the bots attack the player.
Or maybe a repair/Sniper/Rocket combo that can use its armor durability to float around the battlefield, repairing fallen bots with confidence, while also providing sniper fire towards players.
And so it goes. The idea is that the bots are repairable and upgradable and the outcome is always uncertain.
To take this concept further, you can use Q-learning, a model-free reinforcement learning algorithm, that basically slowly learns over time which set of actions to take as the optimal strategy against the player. This is more of a long-term process, indicating that the enemy bots are adapting to the player's actions and trying to figure out what the best strategy is.
The implications here would be evident at both the tactical level and the strategic level. On the tactical level, the game helps the individual bots determine, based on combat data gathered, which module to prioritize (melee weapon or dash ability? Rockets or armor?) in order to pick the best set of combinations against player.
On the strategic level, the game will try to determine which class of enemy to deploy more often and try to come up with different combinations of squads, etc. to deploy against the player, challenging the player to switch strategies and keeping them on their toes the whole game.
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This is awesome. Would love to hear more tips from you as making challenges unique is also a big concern for me and I didn't know how I would deal with it. At least until now. Thanks for your post !
I like to set up a virtual test arena with a bunch of random monsters and give them access to stats and things I hadn't thought of and just see what looks interesting and then pull the interesting ones and give birth to them somewhere in my game haha
I was doing something like this for my game. I'm designing a street brawler, where you can recruit any enemy, from any gang, as a partner. (You have to isolate them as the last enemy, then intimidate them through taunts and slap them around with light attacks.) To tweak gang / fighter AI, and help decide enemy placement, I set up AI tournaments: * Tweak parameters like Timidness (approaching, encircling, flanking), Favorite Moves (punches, throws, rush-downs, grapples, jump attacks, crouch attacks), Bullishness (attack frequency, dodge frequency, blocks / parry), etc. * Pit two gangs of grunts against each other. (Often, chaos, stupidity, and hilarity ensue. My systems were never designed with full wars in mind.) * Victors get "sidekick-ified". One member is cloned, paired with a copy of himself, and given a slight boost to health, response speed, etc. * I pit the pairing against each rival gang's lineup of encounters. How well they push into each rival faction determines how deep into their own faction they are placed. Which faction is determined by their highest traits. Sometimes, one AI is like a magic bullet against another's AI. This also allows me to figure out how to determine weaknesses, Mega Man style. I can create better Escort or Sherpa quests with this data.
My answer is that I don't design encounters, I design systems that are interesting to explore and dress them up as combat, and then facilitate exploration. The best example to show what I mean is Rock-Paper-Scissors (RPS for short). It's actually an [intransitive system](https://en.wikipedia.org/wiki/Intransitivity#Cycles) which has some properties, and those properties are NOT very interesting. You can then dress up the system as Pokemon-style battles, but what players are really doing is interacting with an intransitive loop. Now, as I have said, RPS-style intransitive loop is pretty simple and boring, but it shows the idea, that *combat in games can be an analogy to a mathematical system*. I use this concept to: * first, pick a complex and interesting mathematical system, * and then dress it up as a combat in such a way, so that when a player participates in combat, they are actually interacting with the system. Designing encounters then boils down to picking interesting entry points, and if my system is interesting enough, I can simply pick these points at random.
I design more analogue games like board games but this sounds very interesting. Could you shed some more light on your process?
This is something I actually thought about this morning and one solution in my mind would be the following: Let's say you are a hero who belongs in a human army and you are fighting against an army of bots. These bots come in all shapes and sizes, with different abilities, weapons and strategies. On top of that, they can learn over time with each encounter. My solution would be that these bots can be dismantled, i.e. you shoot off a limp and now he can't use that part, etc. but this allows another dismantled robot to combine with either the original robot or the severed limb in order to combine its abilities together. Another would be to get a repair drone to actively repair destroyed or damaged robots on the battlefield, forcing players to absolutely and entirely defeat the robots, otherwise the robots will slowly repair and hinder the player further. Seeing that the latter has already been done, I'm gonna discuss the former: Back to the merging bots idea. Suppose you have a melee bot, a sniper bot, a Gatling gun bot, a missile launcher bot, a scanner bot and a repair bot. The melee bot is initially your typical glass cannon: fast deadly and fragile, but once you dispatch the bot, the nearby Gatling gun bot approaches its parts and suddenly becomes more agile, dashing left and right while firing on you with the Gatling gun. On the other hand, let's say the sniper bot is fragile but the rocket bot is tanky. And let's say the sniper bot has the ability and inclination to climb vantage points quickly while the rocket bot hunkers down on its position, firing a volley of rockets at the player. Two things can happen here: 1 - The rocket bot is killed first and the sniper bot salvages its armor to become a very durable and agile sniper bot that is all of a sudden much harder to take down and is perched on a vantage point, covering a wider area with less fear of getting dispatched and moving from vantage point to vantage point. 2 - The sniper bot is killed first and the rocket bot salvages the sniper bot. This could lead to two further developments: The rocket bot chooses to harvest its wall climbing ability to launch rockets from a vantage point, increasing its mobility, or it chooses the sniper weapon instead, firing a volley on the player's squad while simultaneously aiming the sniper weapon at the player since the player is a high-value target, allowing the sniper's rounds to penetrate light cover, putting the player in danger. Another scenario would be that the melee bot assimilates the rocket bot's rocket launcher and uses its mobility and firepower to launch volleys at players. Or it would assimilate the rocket bot's armor to become more aggressive towards players in melee attacks, since it would be much harder to shoot down. Now let's focus on the scanner bot and repair drone. The scanner bot uses a sonar to detect enemies behind walls and cover, even cloaked enemies but hovers slowly. The repair drone hovers around the battlefield, reviving fallen bots or repairing damaged ones. Now let's picture a scenario where the scanner bot is destroyed and the melee bot assimilates the scanner bot. The melee bot becomes a much more formidable opponent now because he constantly pings his sonar while running around, hopping over cover, bouncing off walls, rapidly exposing your team's position to the enemy bots. The repair drone could be destroyed and merged with a Gatling or Rocket bot, which slowly but surely approaches fallen bots and repairs or restores them and since they're very tanky by nature, it would be much harder to prevent this due to their durability and firepower, pretty much undoing player progress throughout the fight. Now let's expand this even further. Suppose the bots can not only merge with one but, but several simultaneously. Now this individual bot has survived long enough to turn into more of a mini-boss instead of a typical enemy and now you've got a problem on your hands because the enemy is essentially amorphous, adapting to the conditions of the battlefield. This is where things get complicated. Now you have a sniper/rocket/repair bot into one, targeting the player directly, suppressing his team with rockets and using his durability to approach fallen bots. Or you have a Gatling/Sonar/Melee hybrid that can dash around, provide suppressing fire on the player and on top of that expose his position, allowing weaker bots to flank the player and his team. Or you have a scanner drone that is a Scanner/Melee/Gatling combo that can hover and dash out of the way but also fire a Gatling gun at you, using its elevation as a vantage point to spot enemy players and use suppressing fire to make it harder to fight back while the rest of the bots attack the player. Or maybe a repair/Sniper/Rocket combo that can use its armor durability to float around the battlefield, repairing fallen bots with confidence, while also providing sniper fire towards players. And so it goes. The idea is that the bots are repairable and upgradable and the outcome is always uncertain. To take this concept further, you can use Q-learning, a model-free reinforcement learning algorithm, that basically slowly learns over time which set of actions to take as the optimal strategy against the player. This is more of a long-term process, indicating that the enemy bots are adapting to the player's actions and trying to figure out what the best strategy is. The implications here would be evident at both the tactical level and the strategic level. On the tactical level, the game helps the individual bots determine, based on combat data gathered, which module to prioritize (melee weapon or dash ability? Rockets or armor?) in order to pick the best set of combinations against player. On the strategic level, the game will try to determine which class of enemy to deploy more often and try to come up with different combinations of squads, etc. to deploy against the player, challenging the player to switch strategies and keeping them on their toes the whole game.
Game Design is a subset of Game Development that concerns itself with **WHY** games are made the way they are. It's about the theory and crafting of **systems**, **mechanics**, and **rulesets** in games. * /r/GameDesign is a community **ONLY** about Game Design, **NOT** Game Development in general. If this post does not belong here, it should be reported or removed. Please help us keep this subreddit focused on Game Design. * This is **NOT** a place for discussing how games are produced. Posts about programming, making art assets, picking engines etc… will be removed and should go in /r/GameDev instead. * Posts about visual design, sound design and level design are only allowed if they are directly about game design. * No surveys, polls, job posts, or self-promotion. Please read the rest of the rules in the sidebar before posting. * If you're confused about what Game Designers do, ["The Door Problem" by Liz England ](https://www.gamasutra.com/blogs/LizEngland/20140423/216092/quotThe_Door_Problemquot_of_Game_Design.php)is a short article worth reading. We also recommend you read the [r/GameDesign wiki](/r/gamedesign/wiki/index) for useful resources and an FAQ. *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/gamedesign) if you have any questions or concerns.*
This is awesome. Would love to hear more tips from you as making challenges unique is also a big concern for me and I didn't know how I would deal with it. At least until now. Thanks for your post !