Let us consider an ordered vector A[1 : n]. If the cost of testing each position is similar, then the standard binary search is the best strategy to search the vector. This is true...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
We propose a new lattice reduction method. Our algorithm approximates shortest lattice vectors up to a factor ≤ (k/6)n/2k and makes use of Grover’s quantum search algorithm. Th...
Distributed Constraints Optimization (DCOP) is a powerful framework for representing and solving distributed combinatorial problems, where the variables of the problem are owned b...
Alon Grubshtein, Roie Zivan, Tal Grinshpoun, Amnon...
We describe a new approximation algorithm for solving partially observable MDPs. Our bounded policy iteration approach searches through the space of bounded-size, stochastic fini...