Learning to plan in continuous domains
Artificial Intelligence
Case-based reasoning
Artificial fishes: physics, locomotion, perception, behavior
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
The Utility Problem Analysed: A Case-Based Reasoning Perspective
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
ICCBR '95 Proceedings of the First International Conference on Case-Based Reasoning Research and Development
Animat vision: Active vision in artificial animals
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Stratified case-based reasoning: reusing hierarchical problem solving episodes
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
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This paper presents our current efforts toward development of highlevel behavior routines and motion strategies for the stepwise case-based reasoning (SCBR) approach. The SCBR approach provides an appropriate architectural framework for autonomous navigation system in which situation cases are used to support the situation module, and route cases are used to support the high-level route planning module. In the SCBR approach, adaptation knowledge comes in the form of high-level behavior routines and motion strategies. The SCBR system determines next action based on an analysis of the generated view in terms of positions of relevant objects. Thus, higher-level case-based symbolic reasoning intervenes at the action selection points to determine which action vector is appropriate to control the SCBR system. In order to qualitatively evaluate the SCBR approach, we have developed a simulation environment. This simulation environment allows us to visually evaluate the progress of an SCBR system while it runs through a predefined virtual world.