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» Synthesis for PCTL in Parametric Markov Decision Processes
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AAAI
2004
14 years 11 months ago
Dynamic Programming for Partially Observable Stochastic Games
We develop an exact dynamic programming algorithm for partially observable stochastic games (POSGs). The algorithm is a synthesis of dynamic programming for partially observable M...
Eric A. Hansen, Daniel S. Bernstein, Shlomo Zilber...
ROBOCUP
2007
Springer
99views Robotics» more  ROBOCUP 2007»
15 years 3 months ago
Instance-Based Action Models for Fast Action Planning
Abstract. Two main challenges of robot action planning in real domains are uncertain action effects and dynamic environments. In this paper, an instance-based action model is lear...
Mazda Ahmadi, Peter Stone
ICRA
2010
IEEE
163views Robotics» more  ICRA 2010»
14 years 8 months ago
Exploiting domain knowledge in planning for uncertain robot systems modeled as POMDPs
Abstract— We propose a planning algorithm that allows usersupplied domain knowledge to be exploited in the synthesis of information feedback policies for systems modeled as parti...
Salvatore Candido, James C. Davidson, Seth Hutchin...
SIGMETRICS
2010
ACM
195views Hardware» more  SIGMETRICS 2010»
15 years 1 months ago
CWS: a model-driven scheduling policy for correlated workloads
We define CWS, a non-preemptive scheduling policy for workloads with correlated job sizes. CWS tackles the scheduling problem by inferring the expected sizes of upcoming jobs bas...
Giuliano Casale, Ningfang Mi, Evgenia Smirni