Difference between revisions of "Goal-Driven Personal Development"
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== Using the pattern == | == Using the pattern == | ||
| − | [[Goal-Driven Personal Development]] is created by providing [[Agents]] with goals whose success, failure, and progress can be measured through the game state of a game. For human [[Agents]], this is typically done through letting them select [[Quests]] and making sure that some one these build upon the previous ones to create chains which makes the development over time noticeable. For [[Algorithmic Agents]], [[Quests]] can be used also but typically these need to be more granular in detail and have much more encoding of benefits and requirements available – this to a level which would make them very unlike the [[Quests]] presented to human players. | + | [[Goal-Driven Personal Development]] is created by providing [[Agents]] with goals whose success, failure, and progress can be measured through the game state of a game and that build upon each other in some form. For human [[Agents]], this is typically done through letting them select [[Quests]] and making sure that some one these build upon the previous ones to create chains which makes the development over time noticeable. For [[Algorithmic Agents]], [[Quests]] can be used also but typically these need to be more granular in detail and have much more encoding of benefits and requirements available – this to a level which would make them very unlike the [[Quests]] presented to human players. |
=== Narration Aspects === | === Narration Aspects === | ||
Revision as of 15:06, 26 October 2015
The ability of agents to update their goals after the closure of existing goals.
Note: Goal-Driven Personal Development looks at goals defined through making a game state fulfill certain criteria and therefore excludes many other types of goals agents playing games can have, e.g. social or experiential ones.
Contents
Examples
Using the pattern
Goal-Driven Personal Development is created by providing Agents with goals whose success, failure, and progress can be measured through the game state of a game and that build upon each other in some form. For human Agents, this is typically done through letting them select Quests and making sure that some one these build upon the previous ones to create chains which makes the development over time noticeable. For Algorithmic Agents, Quests can be used also but typically these need to be more granular in detail and have much more encoding of benefits and requirements available – this to a level which would make them very unlike the Quests presented to human players.
Narration Aspects
One part of making Agents believable is that they have intentionality, i.e. have goals and take actions to make these goals be fulfilled. Goal-Driven Personal Development not only relies on that Agents have goals but update the goals based on how the previous goals succeeded or not, and through this can help create Thematic Consistency by making these Agents believable regarding this issue.
Consequences
The possibility of Goal-Driven Personal Development in a game allows Agents to have their Own Agenda that develop over time. When applied to non-human agents, i.e. Algorithmic Agents, Goal-Driven Personal Development allows these to have Open Destinies and can provide Replayability in making it interesting for players to perceive the differences in outcomes for them in various game instances.
Relations
Can Instantiate
Own Agenda, Thematic Consistency
with Algorithmic Agents
Can Modulate
Can Be Instantiated By
Can Be Modulated By
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Possible Closure Effects
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Potentially Conflicting With
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History
A rewrite of a pattern that was part of the original collection in the paper Gameplay Design Patterns for Believable Non-Player Characters[1].
References
- ↑ Lankoski, P. & Björk, S. (2007) Gameplay Design Patterns for Believable Non-Player Characters. Proceedings of DiGRA 2007.
