A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots
Machine Learning - Special issue on learning in autonomous robots
Learning from History for Behavior-Based Mobile Robots in Non-Stationary Conditions
Machine Learning - Special issue on learning in autonomous robots
Multi-Robot Task Allocation in Uncertain Environments
Autonomous Robots
Applying Inexpensive AI Techniques to Computer Games
IEEE Intelligent Systems
Hierarchical planning in a mobile robot for map learning and navigation
Autonomous robotic systems
Tunably decentralized algorithms for cooperative target observation
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Distributed algorithms for multi-robot systems
Proceedings of the 6th international conference on Information processing in sensor networks
Behavior-oriented views of intelligence: models and systems for complex autonomous agents
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Pure reactive behavior learning using Case Based Reasoning for a vision based 4-legged robot
Robotics and Autonomous Systems
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Behavior based autonomous navigation using passages as landmarks for path definition
ACMOS'10 Proceedings of the 12th WSEAS international conference on Automatic control, modelling & simulation
Integrating grid-based and topological maps for mobile robot navigation
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Interference as a tool for designing and evaluating multi-robot controllers
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Application of collective robotic search using neural network based dual heuristic programming (DHP)
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Hi-index | 0.00 |
We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, empirically evaluating, and combining behaviors from a basic set. We also introduce a general methodology for automatically constructing higher-- level behaviors by learning to select from this set. Based on a formulation of reinforcement learning using conditions, behaviors, and shaped reinforcement, out approach makes behavior selection learnable in noisy, uncertain environments with stochastic dynamics. All described ideas are validated with groups of up to 20 mobile robots performing safe-- wandering, following, aggregation, dispersion, homing, flocking, foraging, and learning to forage.