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» Abstraction in Predictive State Representations
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ICMLA
2010
15 years 3 months ago
Incremental Learning of Relational Action Rules
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Christophe Rodrigues, Pierre Gérard, C&eacu...
CAISE
2011
Springer
14 years 9 months ago
Supporting Dynamic, People-Driven Processes through Self-learning of Message Flows
Abstract. Flexibility and automatic learning are key aspects to support users in dynamic business environments such as value chains across SMEs or when organizing a large event. Pr...
Christoph Dorn, Schahram Dustdar
ISI
2007
Springer
16 years 10 days ago
Making Sense of VAST Data
: We view the task of sensemaking in intelligence as that of abducing a story whose plot explains the current data and makes verifiable predictions about the future and the past. W...
Summer Adams, Ashok K. Goel
IPSN
2004
Springer
15 years 11 months ago
Distributed particle filters for sensor networks
Abstract. This paper describes two methodologies for performing distributed particle filtering in a sensor network. It considers the scenario in which a set of sensor nodes make m...
Mark Coates
TACAS
2001
Springer
119views Algorithms» more  TACAS 2001»
15 years 10 months ago
Compositional Message Sequence Charts
Abstract. A message sequence chart (MSC) is a standard notation for describing the interaction between communicating objects. It is popular among the designers of communication pro...
Elsa L. Gunter, Anca Muscholl, Doron Peled