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PERCOM
2007
ACM
16 years 3 months ago
Sensor Scheduling for Optimal Observability Using Estimation Entropy
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
Mohammad Rezaeian
ALT
2006
Springer
16 years 23 days ago
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an age...
Daniil Ryabko, Marcus Hutter
ATAL
2007
Springer
15 years 7 months ago
Interactive dynamic influence diagrams
This paper extends the framework of dynamic influence diagrams (DIDs) to the multi-agent setting. DIDs are computational representations of the Partially Observable Markov Decisio...
Kyle Polich, Piotr J. Gmytrasiewicz
JAIR
2008
145views more  JAIR 2008»
15 years 3 months ago
Communication-Based Decomposition Mechanisms for Decentralized MDPs
Multi-agent planning in stochastic environments can be framed formally as a decentralized Markov decision problem. Many real-life distributed problems that arise in manufacturing,...
Claudia V. Goldman, Shlomo Zilberstein
MKWI
2008
112views Business» more  MKWI 2008»
15 years 5 months ago
A Framework for Querying in Business Process Modelling
: In order to respond quickly to changing market requirements, a business organisation needs to increase the level of agility in all phases of the business process engineering chai...
Ivan Markovic, Alessandro Costa Pereira, Nenad Sto...