Random walks on weighted graphs, and applications to on-line algorithms
STOC '90 Proceedings of the twenty-second annual ACM symposium on Theory of computing
New results on server problems
SIAM Journal on Discrete Mathematics
Journal of Algorithms
An optimal on-line algorithm for metrical task system
Journal of the ACM (JACM)
Memory Versus Randomization in On-line Algorithms (Extended Abstract)
ICALP '89 Proceedings of the 16th International Colloquium on Automata, Languages and Programming
On the complexity of thest-connectivity problem
On the complexity of thest-connectivity problem
Probabilistic computations: Toward a unified measure of complexity
SFCS '77 Proceedings of the 18th Annual Symposium on Foundations of Computer Science
Time-space tradeoffs for undirected graph traversal
SFCS '90 Proceedings of the 31st Annual Symposium on Foundations of Computer Science
Optimal buy-and-hold strategies for financial markets with bounded daily returns
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
A guessing game and randomized online algorithms
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Online variable sized covering
Information and Computation
On-Line Variable Sized Covering
COCOON '01 Proceedings of the 7th Annual International Conference on Computing and Combinatorics
The relative worst-order ratio applied to paging
Journal of Computer and System Sciences
Online scheduling with general cost functions
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
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This paper concerns two fundamental but somewhat neglected issues both related to the design and analysis of randomized online algorithms. Motivated by early results in game theory we define several types of randomized online algorithms discuss known conditions for their equivalence and give a natural example distinguishing between two kinds of randomizations. In particular we show that mixed randomized memoryless paging algorithms can achieve strictly better competitive performance than behavioral randomized algorithms. Next we summarize known-and derive new-"Yao Principle" theorems for lower bounding competitive ratios of randomized online algorithms. This leads to six different theorems for bounded/unbounded and minimization/maximization problems.