Difference between revisions of "Algorithmic Agents"

Revision as of 12:13, 26 May 2010

Agents that are described and enacted through algorithms.

Many games worlds contains more entities such as animals, people, monsters, or robots that have behaviors that are not decided by players. To make this possible these entities are instead have more or less complex rules, algorithms, that decide which actions they should take. The simplest only contain a couple of rules taking not consideration to what the other players or entities have done while the most complex have processes for learning under which contexts one should perform what actions.

Examples

Already most of the earliest computer games, including OXO (a computerized version of Tic-Tac-Toe), Asteroids, Space Invaders, and the Bomberman Series made use of algorithms to control opponents to the players. It is still used in many games, e.g. in the Assassin's Creed, God of War, Need for Speed, Doom, Quake series. In these case the Algorithmic Agents are also used to provide opponents but in games such as Fable II, Fallout Series, NetHack, and Torchlight they also control animals that accompany the players' characters.

Algorithmic Agents are also used to provide a basis of behaviors to agents in a game which players can then modify, as for example in the Lemmings and Sims Series, or indirectly controlled, of which the Black & White series is an example. Games such as RoboRally and Space Alert, where players have to choose several actions together before they are enacted, can also be seen as examples of games that use Algorithmic Agents even if the outcomes are fixed if no outside influences interfere with them. In contrast, programming games such as Crobots and P-Robots challenge players to create better algorithms than other players.

The Left 4 Dead Series uses Algorithmic Agents not only for the infected that attack the players' characters, but also to control other player characters if there are not four people available.

Using the pattern

No Player Influence Action Programming

Agents Avatars Initiative Awareness of Surroundings Contextualized Conversational Responses Emotional Attachment Own Agenda Sense of Self Goal-Driven Personal Development Open Destiny Ambiguous Responses Unpredictable Behavior Mules Stimulated Planning Enemies

Companions NPCs

Algorithmic Agents are powerful tools to make sure a game includes Conflict, since game designer can create them with Preventing Goals to the players' goals and be sure that these will be acted upon (which is not always the case when given to players).

Programming games such as Crobots and P-Robots let players have indirect Conflict in the sense that they try to create Algorithmic Agents that are in Conflict with each other due to Elimination goals.

Algorithmic Agents can be used to create AI Players, so that Multiplayer Games can be played with only one (or in some cases zero) players. While this make is possible to make Multiplayer Games into Single-Player Games or

Using Algorthimic Agents in conjunction with the Avatars or Units players control offers distinctly different design opportunities. If they have already been developed to be able to take the role of players when there are not enough humans, as for example in the Left 4 Dead Series, it is easy to

They can be used to support

Diegetic Aspects

Interface Aspects

Narrative Aspects

Consequences

Relations

Can Instantiate

Agents, Mules Conflict

Can Modulate

Can Be Instantiated By

Can Be Modulated By

Potentially Conflicting With

History

New pattern created in this wiki.

References

Acknowledgments

Karl-Petter Åkesson