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IROS
2006
IEEE
121views Robotics» more  IROS 2006»
16 years 18 days ago
Planning and Acting in Uncertain Environments using Probabilistic Inference
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...
Deepak Verma, Rajesh P. N. Rao
SARA
2005
Springer
16 years 1 days ago
Feature-Discovering Approximate Value Iteration Methods
Sets of features in Markov decision processes can play a critical role ximately representing value and in abstracting the state space. Selection of features is crucial to the succe...
Jia-Hong Wu, Robert Givan
ATAL
2004
Springer
15 years 12 months ago
Communication for Improving Policy Computation in Distributed POMDPs
Distributed Partially Observable Markov Decision Problems (POMDPs) are emerging as a popular approach for modeling multiagent teamwork where a group of agents work together to joi...
Ranjit Nair, Milind Tambe, Maayan Roth, Makoto Yok...
HICSS
2003
IEEE
123views Biometrics» more  HICSS 2003»
15 years 12 months ago
Issues in Rational Planning in Multi-Agent Settings
We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents operating in multi-agent environments. We use the...
Piotr J. Gmytrasiewicz
ISLPED
1999
ACM
91views Hardware» more  ISLPED 1999»
15 years 11 months ago
Stochastic modeling of a power-managed system: construction and optimization
-- The goal of a dynamic power management policy is to reduce the power consumption of an electronic system by putting system components into different states, each representing ce...
Qinru Qiu, Qing Wu, Massoud Pedram