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» Metrics for Finite Markov Decision Processes
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ATAL
2007
Springer
15 years 1 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
CDC
2010
IEEE
136views Control Systems» more  CDC 2010»
14 years 4 months ago
The role of social feedback in steady-state performance of human decision making for two-alternative choice tasks
With an eye towards design of human-in-the-loop systems, we investigate human decision making in a social context for tasks that require the human to make repeated choices among fi...
Andrew Reed Stewart, Naomi Ehrich Leonard
AAAI
2010
14 years 11 months ago
Relational Partially Observable MDPs
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
Chenggang Wang, Roni Khardon
ICML
1996
IEEE
15 years 2 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
JAIR
2010
115views more  JAIR 2010»
14 years 8 months ago
An Investigation into Mathematical Programming for Finite Horizon Decentralized POMDPs
Decentralized planning in uncertain environments is a complex task generally dealt with by using a decision-theoretic approach, mainly through the framework of Decentralized Parti...
Raghav Aras, Alain Dutech