Dynamic game difficulty balancing

Dynamic game elements

Some elements of a game that might be changed via dynamic difficulty balancing include:

• Speed of enemies
• Health of enemies
• Frequency of enemies
• Frequency of powerups
• Power of player
• Power of enemies
• Duration of gameplay experience

Approaches

Different approaches are found in the literature to address dynamic game difficulty balancing. In all cases, it is necessary to measure, implicitly or explicitly, the difficulty the user is facing at a given moment. This measure can be performed by a heuristic function, which some authors call "challenge function". This function maps a given game state into a value that specifies how easy or difficult the game feels to the user at a specific moment. Examples of heuristics used are:

• The rate of successful shots or hits
• The numbers of won and lost pieces
• Life points
• Evolution
• Time to complete some task

... or any metric used to calculate a game score. Chris Crawford said "If I were to make a graph of a typical player's score as a function of time spent within the game, that graph should show a curve sloping smoothly and steadily upward. I describe such a game as having a positive monotonic curve". Games without such a curve seem "either too hard or too easy", he said.

Hunicke and Chapman's approach{{cite book

A traditional implementation of such an agent's intelligence is to use behavior rules, defined during game development. A typical rule in a fighting game would state "punch opponent if he is reachable, chase him otherwise". Extending such an approach to include opponent modeling can be made through Spronck et al.′s dynamic scripting,{{cite book

Andrade et al.{{cite book

Demasi and Cruz{{cite book

Other work in the field of DGB is based on the hypothesis that the player-opponent interaction—rather than the audiovisual features, the context or the genre of the game—is the property that contributes the majority of the quality features of entertainment in a computer game.{{cite book

Further studies by Yannakakis and Hallam{{cite book

Caveats

Designing a game that is fair without being predictable is difficult. Andrew Rollings and Ernest Adams cite an example of a game that changed the difficulty of each level based on how the player performed in several preceding levels. Players noticed this and developed a strategy to overcome challenging levels by deliberately playing badly in the levels before the difficult one. The authors stress the importance of covering up the existence of difficulty adaptation so that players are not aware of it.

Uses in video games

Dynamic difficulty (DDA) refers to automated adjustments to make gameplay easier or harder based on player performance, whereas cheating AI involves the game appearing to override realistic mechanics, giving the AI unfair advantages. Some games may have a blend of both of these systems at once.

An early example of difficulty balancing can be found in Zanac, developed in 1986 by Compile. The game featured a unique adaptive artificial intelligence, in which the game automatically adjusted the difficulty level according to the player's skill level, rate of fire, and the ship's current defensive status/capability. Earlier than this can be found in Midway's 1975 Gun Fight coin-op game. This head-to-head shoot-em-up would aid whichever player had just been shot, by placing a fresh additional object, such as a Cactus plant, on their half of the play-field making it easier for them to hide.

Archons computer opponent slowly adapts over time to help players defeat it. Danielle Bunten designed both M.U.L.E. and Global Conquest to dynamically balance gameplay between players. Random events are adjusted so that the player in first place is never lucky and the last-place player is never unlucky.

The first Crash Bandicoot game and its sequels make use of a "Dynamic Difficulty Adjustment" system, slowing down obstacles, giving extra hit points and adding continue points according to the player's number of deaths. According to the game's lead designer Jason Rubin, the goal was to "help weaker players without changing the game for the better players".

Both Insomniac Game's Spyro the Dragon and Ratchet and Clank series make use of dynamic difficulty with a system termed Automatic Challenge Tuning(ACT). In some cases, in the first released versions of these games, malfunctions in this system resulted in the player being unable to complete the game 100% due to programming oversights.

The video game Flow was notable for popularizing the application of mental immersion (also called flow) to video games with its 2006 Flash version. The video game design was based on the master's thesis of one of its authors, and was later adapted to PlayStation 3.

SiN Episodes released in 2006 featured a "Personal Challenge System" where the numbers and toughness of enemies faced would vary based on the performance of the player to ensure the level of challenge and pace of progression through the game. The developer, Ritual Entertainment, claimed that players with widely different levels of ability could finish the game within a small range of time of each other.

In 2005, Resident Evil 4 employed a system called the "Difficulty Scale", unknown to most players, as the only mention of it was in the Official Strategy Guide. This system grades the player's performance on a number scale from 1 to 10, and adjusts both enemy behavior/attacks used and enemy damage/resistance based on the player's performance (such as deaths, critical attacks, etc.). The selected difficulty levels lock players at a certain number; for example, on Normal difficulty, one starts at Grade 4, can move down to Grade 2 if doing poorly, or up to Grade 7 if doing well. The grades between difficulties can overlap.{{cite book

God Hand, a 2006 video game developed by Clover Studio, directed by Resident Evil 4 director Shinji Mikami, and published by Capcom for the PlayStation 2, features a meter during gameplay that regulates enemy intelligence and strength. This meter increases when the player successfully dodges and attacks opponents, and decreases when the player is hit. The meter is divided into four levels, with the hardest level called "Level DIE." The game also has three difficulties, with the easy difficulty only allowing the meter to ascend to level 2, while the hardest difficulty locks the meter to level DIE. This system also offers greater rewards when defeating enemies at higher levels.

The 2008 video game Left 4 Dead uses an artificial intelligence technology dubbed "The AI Director".{{cite web | archive-url = https://web.archive.org/web/20090327034239/http://www.l4d.com/info.html | archive-date = 2009-03-27 | access-date = 2009-03-16 | archive-date = 2012-02-20 | archive-url = https://web.archive.org/web/20120220154533/http://www.left4dead411.com/left-4-dead-preview-pg2/ | url-status = live |archive-url = https://archive.today/20120909153756/http://www.next-gen.biz/opinion/gabe-newell-writes-edge |url-status = dead |archive-date = 9 September 2012 |access-date = 2008-11-22

Madden NFL 09 introduces "Madden IQ", which begins with an optional test of the players knowledge of the sport, and abilities in various situations. The score is then used to control the game's difficulty.

In the match-3 game Fishdom, the time limit is adjusted based on how well the player performs. The time limit is increased should the player fail a level, making it possible for any player to beat a level after a few tries.

In the 1999 video game Homeworld, the number of ships that the AI begins with in each mission will be set depending on how powerful the game deems the player's fleet to be. Successful players have larger fleets because they take fewer losses. In this way, a player who is successful over a number of missions will begin to be challenged more and more as the game progresses.

In Fallout: New Vegas and Fallout 3, as the player increases in level, tougher variants of enemies, enemies with higher statistics and better weapons, or new enemies will replace older ones to retain a constant difficulty, which can be raised, using a slider, with experience bonuses and vice versa in Fallout 3. This can also be done in New Vegas, but there is no bonus to increasing or decreasing the difficulty.

The Mario Kart series features items during races that help an individual driver get ahead of their opponents. These items are distributed based on a driver's position in a way that is an example of dynamic game difficulty balancing. For example, a driver near the bottom of the field is likely to get an item that will drastically increase their speed or sharply decrease the speed of their opponents, whereas a driver in first or second place can expect to get these kinds of items rarely (and will probably receive the game's weaker items). The game's computer racers also adapt to the player's speed - slowing down when the leading player racer is too far behind the best computer racer, and vice versa - as the rival computer racers catch up to the player in first.

Alleged use to shape player buying behaviour

In 2020, a class-action lawsuit in the United States District Court for the Northern District of California accused game developer Electronic Arts of using its patented Dynamic Difficulty Adjustment technology in three of its EA Sports franchises — Madden NFL, FIFA, and NHL — across all games ranging back to the 2017 versions. The plaintiffs say that EA uses this technology to push players into purchasing more loot boxes in the form of Player Packs, saying that it effectively makes even high-stat players not play as well as they should.

The suit also notes that EA uses this technology without disclosing it to players, noting that EA has denied its use in the past in multiple games mentioned in the suit. When asked for comment on the allegations, EA called the claims "baseless" and that they "misrepresent our games." The plaintiffs voluntarily dismissed the lawsuit in 2021.

References

References

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19. Fitzgerald, Jack. (2021-02-11). "Notice of Voluntary Dismissal of Action Without Prejudice".