Difference between revisions of "Experimenting"
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+ | [[Experimenting]] relies on the presence of [[Gain Information]] or [[Gain Competence]] goals that players can try to complete by performing different variations of actions in a game, but this is not enough since harsh [[Penalties]] for failure may make players cautious. | ||
Experimenting is a form of Gain Information goal and as such requires Imperfect Information. The Imperfect Information can be about the fundamental rules of cause and effect in computer games, about the long-term consequences of actions, or about the game state. In the first two cases, gaining the Imperfect Information gives Strategic Knowledge about the Predictable Consequences in the game, while the last case can provide information about other players' game elements and tactics. The actual actions used in the Experimenting can be any; with Experimenting, players learnabout the actions by performing them. However, it is especially common with Experimenting when doing Puzzle Solving , finding possible Combos, or trying to find Achilles' Heels of Enemies. | Experimenting is a form of Gain Information goal and as such requires Imperfect Information. The Imperfect Information can be about the fundamental rules of cause and effect in computer games, about the long-term consequences of actions, or about the game state. In the first two cases, gaining the Imperfect Information gives Strategic Knowledge about the Predictable Consequences in the game, while the last case can provide information about other players' game elements and tactics. The actual actions used in the Experimenting can be any; with Experimenting, players learnabout the actions by performing them. However, it is especially common with Experimenting when doing Puzzle Solving , finding possible Combos, or trying to find Achilles' Heels of Enemies. |
Revision as of 09:53, 15 August 2011
Exploratory actions to learn how the rules of cause and effect work in a game.
This pattern is a still a stub.
In all but the most simple of games, the complete consequences from actions performed are difficult to understand, but Experimenting can aid in understanding them. Actions may be tested for this reason simply because they have not been tested before if a player is willing to see a game session primarily as a learning period. Some games explicitly build experimenting into gameplay as puzzles. In these cases, the actions used to test possible solutions are usually reversible.
Contents
Examples
Gameplay in Mastermind consists of one player guessing the correct combination of colored pegs. As the chance for guessing correctly based only on luck is very small, successful gameplay requires that the player combines the results from different guesses to draw conclusions and uses the guesses as experiments.
In Pontifex, players' goals are to build bridges and to learn how the physics model works. The players' have to experiment with how cable, joints, and metal beams interact.
The Incredible Machine game series lets players use a limit set of objects such as pipes, bowling balls, cats, candles, ropes, and balloons to try and reach goal states by making the objects interact with each other in certain ways.
The abstract game Zendo require players to set up arrangements of different colored pyramids to extrapolate the correct arrangement rules that a game master has decided to use for that particular game instance.
Creating potions in The Elder Scrolls III: Morrowind can be an experiment if the player is not an alchemist master, as not all effects of ingredients are known until one reaches that level.
Using the pattern
ref to Gees learning principle and Linderoth's paper
Experimenting relies on the presence of Gain Information or Gain Competence goals that players can try to complete by performing different variations of actions in a game, but this is not enough since harsh Penalties for failure may make players cautious.
Experimenting is a form of Gain Information goal and as such requires Imperfect Information. The Imperfect Information can be about the fundamental rules of cause and effect in computer games, about the long-term consequences of actions, or about the game state. In the first two cases, gaining the Imperfect Information gives Strategic Knowledge about the Predictable Consequences in the game, while the last case can provide information about other players' game elements and tactics. The actual actions used in the Experimenting can be any; with Experimenting, players learnabout the actions by performing them. However, it is especially common with Experimenting when doing Puzzle Solving , finding possible Combos, or trying to find Achilles' Heels of Enemies.
In order to encourage Experimenting, the actions should not have severe consequences. In Quick Games, this may not be a problem if the outcome of the game has no Extra-Game Consequences, as a new game session can be started again. In other forms of games, Experimenting is encouraged by having Reversability of actions, either by allowing Save-Load Cycles or avoiding Irreversible Actions. This is typically easier to do in games with Dedicated Game Facilitators, as they can easily restore game states and not require players to do so. Actions that are closely related to Constructive Play, for example Construction, are better suited for Experimenting, because these actions are less likely to result in Competition. Providing Reversability in certain locations, which can be seen as a form of Safe Havens, allows for Smooth Learning Curves, as players can train and gain a certain level of Game Mastery before having to risk failure.
When Experimenting can have severe consequences, they create Tension and can require Leaps of Faith but also encourage Stimulated Planning. Competition puts players in situations where the effect of every action can have the potential of affecting the overall outcome of the Competition, and due to this act of Experimenting, these situations force players to make Risk/Reward choices between the potential benefits of the experiment against the possible loss of not performing the most optimal action.
Can Be Instantiated By
Arithmetic Progression, Safe Havens, Stimulated Planning, Testing Achievements
Combos together with Construction or Hidden Rules
Enemies together with Achilles' Heels or Vulnerabilities
Predictable Consequences together with Limited Foresight
Single-Player Games together with Reversibility or Save-Load Cycles
Can Be Modulated By
Diegetic Aspects
Interface Aspects
Narrative Aspects
Consequences
The act of planning and Experimenting promotes Cognitive Immersion and can modulate the Right Level of Difficulty of a game. As the actions performed when Experimenting do not usually fulfill a goal in the game, the activity gives Illusionary Rewards, but these can be valuable for gameplay since they may provide Strategic Knowledge.
The possibility of Experimenting in a game can aid in avoiding the emergence of Analysis Paralysis, as players can try the effects and consequences of their ideas and plans rather than try to deduce the effects and consequences. This can provide Smooth Learning Curves.
Using Non-Renewable Resources when Experimenting can be costly but encourage Stimulated Planning, unless the game allows players to use Save-Load Cycles.
Can Instantiate
Can Modulate
Challenging Gameplay, Strategic Knowledge
Potentially Conflicting With
Irreversible Events, Randomness
Relations
Can Instantiate
Can Modulate
Challenging Gameplay, Strategic Knowledge
Can Be Instantiated By
Arithmetic Progression, Gain Competence, Gain Information, Safe Havens, Stimulated Planning, Testing Achievements
Combos together with Construction or Hidden Rules
Enemies together with Achilles' Heels or Vulnerabilities
Predictable Consequences together with Limited Foresight
Single-Player Games together with Reversibility or Save-Load Cycles
Can Be Modulated By
Possible Closure Effects
-
Potentially Conflicting With
Irreversible Events, Randomness
History
An updated version of the pattern Experimenting that was part of the original collection in the book Patterns in Game Design[1].
References
- ↑ Björk, S. & Holopainen, J. (2004) Patterns in Game Design. Charles River Media. ISBN1-58450-354-8.
Acknowledgements
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