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AAAI
2010
15 years 9 months ago
Integrating Sample-Based Planning and Model-Based Reinforcement Learning
Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...
INFSOF
2006
103views more  INFSOF 2006»
15 years 7 months ago
Improving test quality using robust unique input/output circuit sequences (UIOCs)
In finite state machine (FSM) based testing, the problem of fault masking in the unique input/output (UIO) sequence may degrade the test performance of the UIO based methods. This...
Qiang Guo, Robert M. Hierons, Mark Harman, Karnig ...
CORR
2011
Springer
183views Education» more  CORR 2011»
15 years 2 months ago
Detecting Separation in Robotic and Sensor Networks
In this paper we consider the problem of monitoring detecting separation of agents from a base station in robotic and sensor networks. Such separation can be caused by mobility an...
Chenda Liao, Harshavardhan Chenji, Prabir Barooah,...
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STTT
2010
120views more  STTT 2010»
15 years 2 months ago
Solving the ignoring problem for partial order reduction
Abstract. Partial order reduction limits the state explosion problem that arises in model checking by limiting the exploration of redundant interleavings. A state space search algo...
Sami Evangelista, Christophe Pajault
AAAI
2012
13 years 10 months ago
Planning in Factored Action Spaces with Symbolic Dynamic Programming
We consider symbolic dynamic programming (SDP) for solving Markov Decision Processes (MDP) with factored state and action spaces, where both states and actions are described by se...
Aswin Raghavan, Saket Joshi, Alan Fern, Prasad Tad...