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Cited by 375

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Multi-level direction of autonomous creatures for real-time virtual environments

Open access
Blumberg, Bruce M., Galyean, Tinsley A.·1995·Proceedings of the 22nd annual conference on Computer graphics and interactive techniques - SIGGRAPH '95

Abstract

There have been several recent efforts to build behavior-based autonomous creatures.While competent autonomous action is highly desirable, there is an important need to integrate autonomy with "directability".In this paper we discuss the problem of building autonomous animated creatures for interactive virtual environments which are also capable of being directed at multiple levels.We present an approach to control which allows an external entity to "direct" an autonomous creature at the motivational level, the task level, and the direct motor level.We also detail a layered architecture and a general behavioral model for perception and action-selection which incorporates explicit support for multi-level direction.These ideas have been implemented and used to develop several autonomous animated creatures.

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Metadata

Authors
Blumberg, B. M., & Galyean, T. A.
Venue
Proceedings of the 22nd annual conference on Computer graphics and interactive techniques - SIGGRAPH '95
Publisher
ACM Press
Published
1995
Pages
47-54
OpenAlex
W2234200704
Cited by
375
References
20
FWCI
70.57
Type
conference paper
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Multi-level direction of autonomous creatures for real-time virtual environments. https://app.cochat.ai/papers/10.1145/218380.218405
The paper
Blumberg, B. M., & Galyean, T. A. (1995). Multi-level direction of autonomous creatures for real-time virtual environments. Proceedings of the 22nd annual conference on Computer graphics and interactive techniques - SIGGRAPH '95. https://doi.org/10.1145/218380.218405

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.