C4.5: programs for machine learning
C4.5: programs for machine learning
Techniques for Plan Recognition
User Modeling and User-Adapted Interaction
Probabilistic State-Dependent Grammars for Plan Recognition
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Robust agent teams via socially-attentive monitoring
Journal of Artificial Intelligence Research
A general model for online probabilistic plan recognition
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Utility-based plan recognition: an extended abstract
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Robust and efficient plan recognition for dynamic multi-agent teams
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Incremental Generation of Abductive Explanations for Tactical Behavior
RoboCup 2007: Robot Soccer World Cup XI
OMBO: An opponent modeling approach
AI Communications
A probabilistic plan recognition algorithm based on plan tree grammars
Artificial Intelligence
Incorporating observer biases in keyhole plan recognition (efficiently!)
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Hypothesis pruning and ranking for large plan recognition problems
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Activity recognition with intended actions
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Delaying commitment in plan recognition using combinatory categorial grammars
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A hybrid plan recognition model for Alzheimer's patients: Interleaved-erroneous dilemma
Web Intelligence and Agent Systems
Activity Recognition for Dynamic Multi-Agent Teams
ACM Transactions on Intelligent Systems and Technology (TIST)
Plan recognition in exploratory domains
Artificial Intelligence
Affordance-Based intention recognition in virtual spatial environments
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
Goal recognition over POMDPs: inferring the intention of a POMDP agent
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
A real-time opponent modeling system for rush football
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Controlling the hypothesis space in probabilistic plan recognition
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Recent applications of plan recognition face several open challenges: (i) matching observations to the plan library is costly, especially with complex multi-featured observations; (ii) computing recognition hypotheses is expensive. We present techniques for addressing these challenges. First, we show a novel application of machine-learning decision-tree to efficiently map multi-featured observations to matching plan steps. Second, we provide efficient lazy-commitment recognition algorithms that avoid enumerating hypotheses with every observation, instead only carrying out bookkeeping incrementally. The algorithms answer queries as to the current state of the agent, as well as its history of selected states. We provide empirical results demonstrating their efficiency and capabilities.