Difference between revisions of "Automated Responses"

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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]]. However, the use of [[Automated Responses]] can create the loss of [[Player Agency]].  
 
[[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]]. However, the use of [[Automated Responses]] can create the loss of [[Player Agency]].  
  
[[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]].
+
[[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 Indicators]].
  
 
== Relations ==
 
== Relations ==
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[[Enforced Agent Behavior]],  
 
[[Enforced Agent Behavior]],  
 
[[Player Augmentations]],  
 
[[Player Augmentations]],  
[[Point of Interest Indications]],  
+
[[Point of Interest Indicators]],  
 
[[Smooth Learning Curves]]
 
[[Smooth Learning Curves]]
  

Latest revision as of 09:31, 15 July 2016

Events triggered by game state configurations designed to either inform players or make responses for them.

Many game designs have either wish to ensure players to be aware of certain facts about some specific game states as they occur or want to ensure specific responses by the game elements that players control. Both of these things can be created by Automated Responses, triggered events that the game system executes based on detecting certain game states.

Examples

Encountering boss monsters in some games in the Super Mario series trigger cut scenes where the monsters are clearly presented so players are made aware of their significance.

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. Stronger examples can be found in Multiuser Dungeons such as DragonMud and Kingdoms where players can create Automated Responses by writing code which interprets output from the game and produces input to the game for the players. Ultima Online and World of Warcraft provided similar functionality.

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. Cutscenes and Voice-overs are ways 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.

Typical examples of cases when Automated Responses may be deemed necessary to inform players of future gameplay includes the introduction of Boss Monsters (and perhaps hints of their weaknesses) or forcing attention to Clues or providing addition information to that which they diegetically provide. However, the introduction of whole Levels may also be provided as Automated Responses when they are entered to prepare players of the upcoming gameplay (and perhaps foreshadow gameplay events).

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 a 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. However, the use of Automated Responses can create the loss of Player Agency.

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 Indicators.

Relations

Can Instantiate

Enforced Agent Behavior, Player Augmentations, Point of Interest Indicators, Smooth Learning Curves

with Player/Character Skill Composites

Player/System Action Composites

Can Modulate

Avatars, Boss Monsters, Characters, Chat Channels, Clues, Levels

Can Be Instantiated By

Algorithmic Agents, Cutscenes, Mules, Voice-overs

Can Be Modulated By

Line of Sight

Possible Closure Effects

-

Potentially Conflicting With

Player Agency

History

New pattern created in this wiki.

References

-

Acknowledgements

-