Learn More
We identify a rich class of finite-horizon Markov decision problems (MDPs) for which the variance of the optimal total reward can be bounded by a simple affine function of its expected value. The class is characterized by three natural properties: reward boundedness, existence of a do-nothing action, and optimal action monotonicity. These properties are(More)
Let Xf, 1 < i < 00, be unifonnly distributed in [0, if and let T " be the length of the shortest closed path ccmaecting {Xf,X2,. .. , X "). \t is proved that there is a constant 0< ;8< oo such that for all o 0 This result is esseatial in Justifying Karp's algorithm for the trav«UtBg saksman problrai under the independent model, and it settles a question(More)
We consider the problem of selecting sequentially a unimodal subsequence from a sequence of independent identically distributed random variables, and we find that a person doing optimal sequential selection does so within a factor of the square root of two as well as a prophet who knows all of the random observations in advance of any selections. Our(More)
We search for the technicolor process pp-->rhoT/omegaT-->WpiT in events containing one electron and two jets, in data corresponding to an integrated luminosity of 390 pb(-1), recorded by the D0 experiment at the Fermilab Tevatron. Technicolor predicts that technipions pi(T) decay dominantly into bb, bc, or bc, depending on their charge. In these events b(More)
We prove a central limit theorem for a class of additive processes that arise naturally in the theory of finite horizon Markov decision problems. The main theorem generalizes a classic result of Dobrushin (1956) for temporally non-homogeneous Markov chains, and the principal innovation is that here the summands are permitted to depend on both the current(More)