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  • Replayability: Game Mechanics As Periodic Dilemma Generators

    [01.28.21]
    - Narek Aghekyan

  • Hyper-Casual Game Examples

    Helix Jump

    1. Meaningful choices. The colors and the geometry of the helix clearly shows the deadly and safe sectors providing an informed choice. Choices have consequences as by turning the helix you either go down through the holes or fall on a deadly sector and die.
    2. Dilemmatic choices. There is a triangularity: the player can go down multiple steps and obtain higher speed, making it riskier to land on a safe sector, or go step by step and play less risky and less rewarding gameplay.  The second triangularity is because the game suggests invulnerability (big reward) if you manage to pass multiple steps in a row without landing on any safe sector (big risk).
    3. Unpredictable outcome. You never have a situation in Helix Jump, thinking that it is impossible to win this level, or in spite of your moves you will surely win the level.

    Aquapark.io

    1. Meaningful choices. The player sees the pipe shape, knows his avatar's speed and positions and speeds of other non-player characters (NPC). The control of aquapark.io is consistent, and hence the player has full information of costs and benefits of his actions. Choices, such as avatar movements and physical interactions between avatars create consequences.
    2. Dilemmatic choices. When a player decides to attack an NPC there is a triangularity -  either he succeeds to kick an NPC and eliminates an opponent, or he risks to jump out of the tube and makes it harder to safely land back on the tube, especially if he attacks on the turns. Other triangularity arises, when the player decides to take a shortcut by jumping from the tube, in order to land on the lower parts of the tube or even directly into the pool. 
    3. Unpredictable outcome. Aquapark.io's NPCs are programmed so that if you start the game and watch, you might even get the first place, and vice versa, if you play actively, you might not end the first. This is due to the above mentioned Rubber Bending effect in  the Racing Games section. Therefore, until the last moment of the game, there is no idea if you are going to win or lose the race.

    Physics based games usually have a higher replay value, because it is almost impossible to have the same physics simulation for every repeated session. Also random generation of the level plays a positive role in expanding the possibility space of a game. Both Aquapark.io and Helix Jump utilize these features.

    We can easily and quickly analyze other replayable games too by examining their dilemmatic choices only:

    1. Push'em all's PDG operates on the fact that the closer the player's avatar is to the roof edge, the higher chances he has to push NPC off the roof. But there is a higher risk that either he will fall off, or enemies will kick him off the roof. 
    2. Crash Landing 3D's main dilemma generation happens because there is a limited fuel and the player needs to choose between consuming more fuel and obtaining more control, or vice versa.

    3. Paper.io's PDG operates on the fact that the longer lines the player draws to cover larger areas, the higher is the risk to be killed by other NPCs - again a triangularity.

    4. Archero is a shooter game, and, as described above, there is a dilemma of movement and stopping the movement. Should the player stop movement to start shooting and expose himself to enemy attacks? When should he do that? Where should he do that?

    5. AdVenture Capitalist is one of the simplest idle games ever created. In his blogpost Anthony Pecorella has covered the math behind AdVenture Capitalist and from the article it is clearly shown that the game designer is deliberately trying to hide the optimal choice from the player by using multipliers [10]. In his blogpost Anthony writes: "As you progress through the game, different generators take priority and have the biggest impact on income. The player gets to try to identify these priorities (they won't always be obvious right away), and this provides more variety and less predictability."

    6. Super Mario Bros. Levels in this game are designed so that the best feeling you get is by rushing forward. It is not only about the feeling but also it is easier to pass the level with rushing if you have enough skill to rush properly. The designer has tuned the following parameters to make the rushing playstyle more favorable: enemy positions and speeds,  star power-up behaviour, Lakitu and Hammer Bro and other enemy behaviours, Mario is jumping higher and longer while running, time limit on the level, etc. But it is also harder to play rushing. If you rush it is harder to control, but if you manage to control it is easier to pass the level. If you don't rush, it is easier to control, but the challenges are harder to overcome, and also there is a time pressure. So should the player rush, or not? [1] This is a very good example of how the PDG can be built not into the core of the game but into the level design. Enemies' behavior and the level design are periodically generating dilemmas for the player.

    7. Pac - Man - This game economy is designed so that the enemies are becoming more and more aggressive over time till there is a relaxation period. [5] Over that time the player has a dilemma - to use power pills and attack enemies, or to take a risk and wait by hoping not to consume power pills quickly and save them for harder times.

    Looking through the examples above, it could be concluded that the only way to create dilemmas is by using triangularity. In fact, triangularity is a really good tool for generating a dilemma. Jesse Schell says "I find that about eight out of ten times someone comes to me asking for help on a game prototype that "just isn't fun",  the game is missing this kind of meaningful choice." [7] and, obviously, for a good reason. But triangularity is not the only way of offering dilemmas to the player. A simple example of chess will clarify this. Consider a situation, where you have a choice to capture two different pieces, where capturing one piece will create a strong material advantage, and capturing another one will create a strong tactical advantage. Now this is a dilemma without a triangularity. Another example, in a shooter game you can buy a low damage but a faster shooting weapon, or you can buy a high damage but a slower shooting weapon. Both have advantages and disadvantages, this is a dilemma, but without a triangularity.

    As it was mentioned above PDG is an abstract concept, as it is very precise, unambiguous and you will never meet it in reality in the pure form. But the real world is much more complex and we need to consider that we have utilized this abstraction in order to simplify the situation and be able to deal with it. Later we will also consider the psychology of the player and his perception of a PDG system.

    Using PDGs in Games

    As mentioned above PDG is an abstraction, a simplification of real systems, but this is a very useful tool to model, analyze and understand how games provide high replay value and build our own replayable games. We will use PDG the same way we use point particle or ideal gas abstract and simple concepts in physics to model complex natural phenomena.

    In fact, PDG is transparently describing what is an interesting choice. In order to achieve high replay value, games need to implement PDG systems to periodically generate interesting choices. After examining examples above we already should have a pretty good understanding of what is a PDG but we need to delve into the subtle details to be able to implement PDGs into our games. For that reason let's understand what it means to implement a PDG in a game. In order to understand that we need to not only discuss how PDG can be built into games but also how player's skills and psychology starts to play a role in the perception of the PDG. Let's first discuss PDGs as systems in the core mechanics.

    Implementing a PDG in a game

    So the player starts a game, sets a goal and waits for the game, as an implementation of a PDG system, to present him with choices.  

    1. A game is an interactive system, hence players need to make decisions, or speaking another way, take choices to change the system's state. Choices presented by PDG should be meaningful, i.e. be informed and have consequences in terms of getting closer to the goal. The goal is not necessarily the win or lose criterion. It can be any smaller sub-goal a player might have.
    2. The choices presented to the player should not be obvious - it should be a dilemma. Yes, players feel smart when they see a good choice and take that choice, but if the game will continue to provide with obvious good or obvious bad choices, players will stop feeling smart or even interested. It is well known how dominant strategies ruin the game and how game designers need to balance the game and make sure that there are no obvious good choices. There should always be decisions that players make but they are not sure it was the optimal.
    3. The outcome of the choice should be unpredictable in terms of the player's goal. You might argue that this point contradicts to the point that player choices should be informed. You might ask if it is an informed choice, then how the outcome could be unpredictable? To understand this, think about chess. Before every move a chess player clearly knows what his move will change on the board. But in the long term he is not sure if he will achieve his goal. Professional chess players don't play the game till checkmate. If they identify that the outcome is predictable, i.e. checkmate or draw is unavoidable, they stop playing at that point. The game's outcome stops being unpredictable. In other words, the player should have a hope that he can achieve his goal, but not be sure that he can do that.

    To summarize, a player needs to make not obvious choices, such that he knows the consequences of those choices, but that is not enough to predict the game's outcome.

    The table below presents a schematic example of how a PDG works. On every step the PDG offers choices (column Offered Choices). One of the choices is being selected (column Selected Choice). As a consequence of the selected choice the system changes its state accordingly (column System State). In the next step again some choices are offered. This is done periodically - in a loop. For example, initially the system is in state S. On step 2 the PDG system offers 3 choices - A, B, C. Player selects B choice. After that the system state changes to S + B. All offered choices (A, B, C, D, E) are both meaningful (informed and have consequences) and dilemmatic, but in every state of the system (S, S + B, S + B + D) it is not predictable whether the user of the system will achieve or fail his goal. As long as these conditions are met, we will say we have a PDG system.

    Step NumberOffered ChoicesSelected ChoiceSystem State
    1 - - S
    2 A, B, C B S + B
    3 B, D, E D S + B + D

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