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» Learning Action Strategies for Planning Domains
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EWRL
2008
13 years 8 months ago
Optimistic Planning of Deterministic Systems
If one possesses a model of a controlled deterministic system, then from any state, one may consider the set of all possible reachable states starting from that state and using any...
Jean-François Hren, Rémi Munos
ICMLA
2007
13 years 8 months ago
Learning complex problem solving expertise from failures
Our research addresses the issue of developing knowledge-based agents that capture and use the problem solving knowledge of subject matter experts from diverse application domains...
Cristina Boicu, Gheorghe Tecuci, Mihai Boicu
CORR
2010
Springer
147views Education» more  CORR 2010»
13 years 6 months ago
Learning Probabilistic Hierarchical Task Networks to Capture User Preferences
While much work on learning in planning focused on learning domain physics (i.e., action models), and search control knowledge, little attention has been paid towards learning use...
Nan Li, William Cushing, Subbarao Kambhampati, Sun...
NIPS
1993
13 years 8 months ago
Robust Reinforcement Learning in Motion Planning
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
APIN
2004
81views more  APIN 2004»
13 years 6 months ago
Learning Generalized Policies from Planning Examples Using Concept Languages
In this paper we are concerned with the problem of learning how to solve planning problems in one domain given a number of solved instances. This problem is formulated as the probl...
Mario Martin, Hector Geffner