Action selection

Uses your system voice; voice and rate in settings.

Snapshot

≈ 4 min read

Names in other languages

No names in other languages are held for this entry yet.

Article bodies are English and are not machine-translated. A name in another language is not a translation of the article.

Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, "the action selection problem" is typically associated with intelligent agents and animats—artificial systems that exhibit complex behavior in an agent environment. The term is also sometimes used in ethology or animal behavior. One problem for understanding action selection is determining the level of abstraction used for specifying an "act". At the most basic level of abstraction, an atomic act could be anything from contracting a muscle cell to provoking a war. Typically for any one action-selection mechanism, the set of possible actions is predefined and fixed. Most researchers working in this field place high demands on their agents: * The acting agent typically must select its action in dynamic and unpredictable environments. * The agents typically act in real time; therefore they must make decisions in a timely fashion. * The agents are normally created to perform several different tasks. These tasks may conflict for resource allocation (e.g.…

Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, "the action selection problem" is typically associated with intelligent agents and animats—artificial systems that exhibit complex behavior in an agent environment. The term is also sometimes used in ethology or animal behavior. One problem for understanding action selection is determining the level of abstraction used for specifying an "act". At the most basic level of abstraction, an atomic act could be anything from contracting a muscle cell to provoking a war. Typically for any one action-selection mechanism, the set of possible actions is predefined and fixed. Most researchers working in this field place high demands on their agents: The acting agent typically must select its action in dynamic and unpredictable environments. The agents typically act in real time; therefore they must make decisions in a timely fashion. The agents are normally created to perform several different tasks. These tasks may conflict for resource allocation (e.g. can the agent put out a fire and deliver a cup of coffee at the same time?) The environment the agents operate in may include humans, who may make things more difficult for the agent (either intentionally or by attempting to assist.) The agents themselves are often intended to model animals or humans, and animal/human behaviour is quite complicated. For these reasons, action selection is not trivial and attracts a good deal of research. Champandard, A. J.: AI Game Development: Synthetic Creatures with learning and Reactive Behaviors. New Riders, USA (2003) Grand, S., Cliff, D., Malhotra, A.: Creatures: Artificial life autonomous software-agents for home entertainment. In: Johnson, W. L. (eds.): Proceedings of the First International Conference on Autonomous Agents. ACM press (1997) 22-29 Huber, M. J.: JAM: A BDI-theoretic mobile agent architecture. In: Proceedings of the Third International Conference on Autonomous Agents (Agents'99). Seattle (1999) 236-243 Isla, D.: Handling complexity in Halo 2. In: Gamastura online, 03/11 (2005) Maes, P.: The agent network architecture (ANA). In: SIGART Bulletin, 2 (4), pages 115–120 (1991) Nareyek, A. Excalibur project Reynolds, C. W. Flocks, Herds, and Schools: A Distributed Behavioral Model. In: Computer Graphics, 21(4) (SIGGRAPH '87 Conference Proceedings) (1987) 25–34. de Sevin, E. Thalmann, D.:A motivational Model of Action Selection for Virtual Humans. In: Computer Graphics International (CGI), IEEE Computer SocietyPress, New York (2005) Tyrrell, T.: Computational Mechanisms for Action Selection. Ph.D. Dissertation. Centre for Cognitive Science, University of Edinburgh (1993) van Waveren, J. M. P.: The Quake III Arena Bot. Master thesis. Faculty ITS, University of Technology Delft (2001) Wooldridge, M. An Introduction to MultiAgent Systems. John Wiley & Sons (2002)

Text derived from https://en.wikipedia.org/w/index.php?oldid=1372381717 under CC BY-SA 4.0; modifications have been made.