Difference between revisions of "Automated Responses"
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| − | '' | + | ''Events triggered by game state configurations designed to either inform players or make responses for them.'' |
| − | + | Many games have | |
=== Examples === | === Examples === | ||
| − | + | A weak examples of [[Automated Responses]] is the "look" action in [[:Category:Adventure Games|Adventure Games]] such as [[Maniac Mansion]] and the [[Zork series]], which while they do inform players about game elements are in fact triggered by specific actions by players rather than game state configurations. | |
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== Using the pattern == | == Using the pattern == | ||
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[[Automated Responses]] are ways of modulating [[Avatars]], [[Characters]], or (at least) [[Chat Channels]]. By doing so they can created [[Enforced Agent Behavior]] or provide [[Player Augmentations]]. When they are combined with [[Player/Character Skill Composites]], the resulting effect can become [[Player/System Action Composites]]. | [[Automated Responses]] are ways of modulating [[Avatars]], [[Characters]], or (at least) [[Chat Channels]]. By doing so they can created [[Enforced Agent Behavior]] or provide [[Player Augmentations]]. When they are combined with [[Player/Character Skill Composites]], the resulting effect can become [[Player/System Action Composites]]. | ||
| − | When [[Automated Responses]] brings players' attention to certain features about the current game state, they function as [[Point of Interest Indications]]. | + | [[Automated Responses]] can help players have [[Smooth Learning Curves]]. When [[Automated Responses]] brings players' attention to certain features about the current game state, they function as [[Point of Interest Indications]]. |
== Relations == | == Relations == | ||
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[[Enforced Agent Behavior]], | [[Enforced Agent Behavior]], | ||
[[Player Augmentations]], | [[Player Augmentations]], | ||
| − | [[Point of Interest Indications]] | + | [[Point of Interest Indications]], |
| + | [[Smooth Learning Curves]] | ||
==== with [[Player/Character Skill Composites]] ==== | ==== with [[Player/Character Skill Composites]] ==== | ||
Revision as of 21:31, 4 July 2015
Events triggered by game state configurations designed to either inform players or make responses for them.
Many games have
Contents
Examples
A weak examples of Automated Responses is the "look" action in Adventure Games such as Maniac Mansion and the Zork series, which while they do inform players about game elements are in fact triggered by specific actions by players rather than game state configurations.
Using the pattern
Designing Automated Responses consist of deciding what responses show exist (and why) and when they should be given. The types of responses can be divided into two main categories: the ones that affect the game state and the ones that only inform players about the game state. Voice-overs is one way of creating Automated Responses without affecting game states while Algorithmic Agents and Mules can perform gameplay actions as Automated Responses.
When Automated Responses should be given are typically bound tightly to the specific responses that should be possible, e.g. providing specific information about a game element, or related to it, when it is encountered. Quite naturally, Line of Sight can be used to make the Automated Responses only be made about things the player is actually looking at.
Interface Aspects
As Automated Responses provide information or feedback to players it is an Interface Pattern.
Narration Aspects
Since Automated Responses can provide narration (e.g when used with Voice-overs), the pattern can be an Narration Pattern.
Consequences
Automated Responses are ways of modulating Avatars, Characters, or (at least) Chat Channels. By doing so they can created Enforced Agent Behavior or provide Player Augmentations. When they are combined with Player/Character Skill Composites, the resulting effect can become Player/System Action Composites.
Automated Responses can help players have Smooth Learning Curves. When Automated Responses brings players' attention to certain features about the current game state, they function as Point of Interest Indications.
Relations
Can Instantiate
Enforced Agent Behavior, Player Augmentations, Point of Interest Indications, Smooth Learning Curves
with Player/Character Skill Composites
Player/System Action Composites
Can Modulate
Avatars, Characters, Chat Channels
Can Be Instantiated By
Algorithmic Agents, Mules, Voice-overs
Can Be Modulated By
Possible Closure Effects
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Potentially Conflicting With
History
New pattern created in this wiki.
References
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Acknowledgements
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