Difference between revisions of "Complex Gameplay"

Revision as of 09:35, 14 January 2015

The one-sentence "definition" that should be in italics.

This pattern is a still a stub.

(Right level of complexity)

Examples

Minecraft

Go

Chess

Game of Life Magic: the Gathering both which are Turing equivalent.

Europa Universalis series Crusader Kings series

Nomic

Anti-Examples

optional

Using the pattern

Complex Gameplay can be a design goal for several reasons in game, common ones being to provide Challenging Gameplay, Solution Uncertainty, and, more generally, Cognitive Engrossment. It can also be used to increase or decrease the likelihood of Analysis Paralysis or Stimulated Planning since a certain level of complexity might increase the presence of these patterns but adding even more complexity might decrease them. The generic ways of providing Complex Gameplay is through number of game components (and their relations), through numbers of rules (and their inter-connectivity), and through the number of actions with Predictable Consequences players can perform.

Can Be Instantiated By

Abilities, Algorithmic Agents, Asynchronous Collaborative Actions, Attention Swapping, Budgeted Action Points, Combos, Converters, Dedicated Game Facilitators, Enemies, Evolving Rule Sets, Game Masters, Indirect Control, Internal Rivalry, Movement, Optional Rules, Orthogonal Differentiation, Perfect Information, Producer-Consumer, Puzzle Solving, Red Herrings, Resources, Resource Management, Rhythm-Based Actions, Rock-Paper-Scissors, Role Reversal, Skills, Trumps, Units, Variable Accuracy, Varying Rule Sets

Betrayal together with Cooperation or Teams

Collaborative Actions together with Delayed Effects or Delayed Reciprocity

Limited Resources together with Traverse

Trading together with Delayed Effects

(have below as example for Algorithmic Agents, Dedicated Game Facilitators, or Game Masters)

Non-Player Characters with Algorithmic Agents, Dedicated Game Facilitators, or Game Masters

(have below as example for Enemies and [[Goal Hierarchies)

Quests together with with Enemies or Goal Hierarchies

There are several ways of limiting or adjusting the complexity of gameplay or how players perceive the complexity. Smooth Learning Curves lets players only be exposed to a small part of the whole complexity of a game, and only let them have more complexity after they have proven that they can handle the amount they have been experiencing so far. Exaggerated Perception of Influence or Limited Foresight can make players not be able to perceive the true complexity or be able to try and analyze it. Time Pressure and Limited Planning Ability works similarly but can make players notice the complexity but forcing them to act without completely analyzing the current situation. Ability Losses and Varying Rule Sets can be used to remove complexity during gameplay or create complexity in that players need to make use of different parts of the available actions and rules during different parts of the game. The subsections below for also describe ways this can be done through diegetic, interface, or narration design.

Diegetic Aspects

While breaking Diegetic Consistency, Extra-Game Information can be used to provide players with direct information about how the game system works from within the game and through this both make Complex Gameplay easier to understand and point out game rules that might be missed otherwise.

Interface Aspects

Game State Indicators can provide players with clear presentations of parts of the game state and thereby make it easier to get an overview of what is happening in a game with Complex Gameplay. Similar to Extra-Game Information, Loading Hints and Tooltips can provide players with direct information about how the game system functions.

Narration Aspects

Narration Structures can be used to make Complex Gameplay easier to handle through having the narration provide another level of description that players can make use of to keep track of how various game components (typically Characters) relate to each other.

Consequences

Complex Gameplay can have several different far-reaching consequences for a game design. First, it can lead to Challenging Gameplay and possibly FUBAR Enjoyment. Second, it can lead to Solution Uncertainty and make Predictable Consequences absent so players may be inclined to do Experimenting. This also lead to Complex Gameplay making Surprises possible but at the same time making Anticipation more unlikely. Complex Gameplay has a dual relation to Hovering Closures, it can provide these by having many simultaneously requirements that need to be fulfilled at the same time but when they are too many of these, or their status is not clearly presented, players may not experience them as being close to being reached. The pattern does however not need to lead to both Solution Uncertainty and Challenging Gameplay at the same time, and when a game with Complex Gameplay lacks challenging aspects (at least sometimes), it can provide Creative Control and let players engage in Pottering (Minecraft can be seen as an example of this). Third, the complexity of gameplay can lead to Varied Gameplay since players may only be focusing or interacting with specific parts of the gameplay in each game instance. All these consequences can lead to Cognitive Engrossment so this is perhaps one of the more predictable effects of Complex Gameplay. Finally, being able to handle the complexity of a game with Complex Gameplay is a form of Game Mastery, e.g. when being able to skillfully make use of all possible Combos.

Complex Gameplay can give Excise if players need to manipulate many individual game components as part of gameplay. When the Complex Gameplay relies on Resource Management, this can take the form of Grinding.

Relations

Can Instantiate

Challenging Gameplay, Cognitive Engrossment, Creative Control, Excise, Experimenting, FUBAR Enjoyment, Game Mastery, Hovering Closures, Pottering, Solution Uncertainty, Varied Gameplay

with Resource Management

Grinding

Can Modulate

Analysis Paralysis, Stimulated Planning

Can Be Instantiated By

Abilities, Algorithmic Agents, Asynchronous Collaborative Actions, Attention Swapping, Budgeted Action Points, Combos, Converters, Dedicated Game Facilitators, Enemies, Evolving Rule Sets, Game Masters, Indirect Control, Internal Rivalry, Movement, Optional Rules, Orthogonal Differentiation, Perfect Information, Predictable Consequences, Producer-Consumer, Puzzle Solving, Red Herrings, Resources, Resource Management, Rhythm-Based Actions, Rock-Paper-Scissors, Role Reversal, Skills, Surprises, Trumps, Units, Variable Accuracy, Varying Rule Sets

Betrayal together with Cooperation or Teams

Collaborative Actions together with Delayed Effects or Delayed Reciprocity

Limited Resources together with Traverse

Trading together with Delayed Effects

Can Be Modulated By

Ability Losses, Exaggerated Perception of Influence, Extra-Game Information, Game State Indicators, Limited Foresight, Limited Planning Ability, Loading Hints, Narration Structures, Smooth Learning Curves, Time Pressure, Tooltips, Varying Rule Sets

Possible Closure Effects

-

Potentially Conflicting With

Anticipation, Hovering Closures, Predictable Consequences

History

An heavily updated version of the pattern Right Level of Complexity that was part of the original collection in the book Patterns in Game Design^[1]. The update has made the pattern be rather close to the concept of analytic complexity described in Costikyan's book Uncertainty in Games^[2].

References

1. ↑ Björk, S. & Holopainen, J. (2004) Patterns in Game Design. Charles River Media. ISBN1-58450-354-8.
2. ↑ Costikyan, G. 2013. Uncertainty in Games. MIT Press. Official webpage for the book.

Acknowledgements

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