A Framework for Dynamical Intention in Hybrid Navigating Agents
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Connecting cognitive and physical worlds with dynamic cost function definition
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Action selection and task sequence learning for hybrid dynamical cognitive agents
Robotics and Autonomous Systems
Hybrid system reachability-based analysis of dynamical agents
WRAC'05 Proceedings of the Second international conference on Radical Agent Concepts: innovative Concepts for Autonomic and Agent-Based Systems
| Hi-index | 0.00 |
Animated characters may exhibit several kinds of dynamic intelligence when performing low-level navigation (i.e., navigation on a local perceptual scale): They decide among different modes of behavior, selectively discriminate entities in the world around them, perform obstacle avoidance, etc. In this paper, we present a hybrid dynamical system model of low-level navigation that accounts for the above-mentioned kinds of intelligence. In so doing, the model illustrates general ideas about how a hybrid systems perspective can influence and simplify such reactive/behavioral modeling for multi-agent systems. In addition, we directly employed our formal hybrid system model to generate animations that illustrate our navigation strategies. Overall, our results suggest that hierarchical hybrid systems may provide a natural framework for modeling elements of intelligent animated actors.