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» Fractal Algorithm for Finding Global Optimal Solution
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ICML
2006
IEEE
15 years 10 months ago
Qualitative reinforcement learning
When the transition probabilities and rewards of a Markov Decision Process are specified exactly, the problem can be solved without any interaction with the environment. When no s...
Arkady Epshteyn, Gerald DeJong
ASPDAC
2005
ACM
114views Hardware» more  ASPDAC 2005»
14 years 11 months ago
Redundant-via enhanced maze routing for yield improvement
- Redundant via insertion is a good solution to reduce the yield loss by via failure. However, the existing methods are all post-layout optimizations that insert redundant via afte...
Gang Xu, Li-Da Huang, David Z. Pan, Martin D. F. W...
70
Voted
AAAI
2006
14 years 11 months ago
Probabilistic Temporal Planning with Uncertain Durations
Few temporal planners handle both concurrency and uncertain durations, but these features commonly co-occur in realworld domains. In this paper, we discuss the challenges caused b...
Mausam, Daniel S. Weld
AAAI
2000
14 years 11 months ago
Solving Combinatorial Auctions Using Stochastic Local Search
Combinatorial auctions (CAs) have emerged as an important model in economics and show promise as a useful tool for tackling resource allocation in AI. Unfortunately, winner determ...
Holger H. Hoos, Craig Boutilier
UAI
2000
14 years 11 months ago
The Complexity of Decentralized Control of Markov Decision Processes
We consider decentralized control of Markov decision processes and give complexity bounds on the worst-case running time for algorithms that find optimal solutions. Generalization...
Daniel S. Bernstein, Shlomo Zilberstein, Neil Imme...