Structured circuit semantics for reactive plan execution systems
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
The automated mapping of plans for plan recognition
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
On social laws for artificial agent societies: off-line design
Artificial Intelligence - Special volume on computational research on interaction and agency, part 2
Decision-Theoretic Cooperative Sensor Planning
IEEE Transactions on Pattern Analysis and Machine Intelligence
TAIPE: tactical assistants for interaction planning and execution
AGENTS '97 Proceedings of the first international conference on Autonomous agents
An explicit semantics for coordination multiagent plan execution
An explicit semantics for coordination multiagent plan execution
An architecture for Real-Time Reasoning and System Control
IEEE Expert: Intelligent Systems and Their Applications
Plan-based plan recognition models for the effective coordination of agents through observation
Plan-based plan recognition models for the effective coordination of agents through observation
The YARF system for vision-based road following
Mathematical and Computer Modelling: An International Journal
Modular Models of Intelligence – Review, Limitations and Prospects
Artificial Intelligence Review
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Fielding robots in complex applications can stress thehuman operators responsible for supervising them, particularlybecause the operators might understand the applications but notthe details of the robots. Our answer to this problem has beento insert agent technology between the operator and the roboticplatforms. In this paper, we motivate the challenges indefining, developing, and deploying the agent technology thatprovides the glue in the application of tasking unmanned groundvehicles in a military setting. We describe how a particularsuite of architectural components serves equally well to supportthe interactions between the operator, planning agents, androbotic agents, and how our approach allows autonomy duringplanning and execution of a mission to be allocated among thehuman and artificial agents. Our implementation anddemonstrations (in real robots and simulations) of ourmulti-agent system shows significant promise for the integrationof unmanned vehicles in military applications.