a range of research areas in Operations Research. He is best known for introducing the Hit-and-Run algorithm in 1979 for efficiently sampling points from high dimensional regions which Laszlo Lovasz showed achieved the best performance of all sampling algorithms. Smith and his colleagues introduced Sampled Fictitious Play (SFP) in 2000 for efficiently finding a Nash equilibrium through best replies to draws of other players from historical plays in a series of games of identical interest. Thomas J. Sargent discussed the implications of SFP and other approaches to finding Nash equilibria for Artificial Intelligence in Sources of Artificial Intelligence. A Nash equilibrium can be viewed as a local optimum of an optimization problem seen as an identical interest game. Awards and honors 1997 – Research Excellence Award, Department of Industrial and Operations Engineering 2002 – Distinguished Faculty Achievement Award, University of Michigan 2003 – Altarum/ERIM Russell D. O’Neal Endowed Professorship in Engineering, University of Michigan 2003 – Elected Fellow, Institute for Operations Research and the Management Sciences Bibliography Selected articles Smith, R. L. (1984). Efficient Monte Carlo procedures for generating points uniformly distributed over bounded regions. Operations Research, 32(6), 1296–1308. Bean, J. C. & Smith, R.L. (1984). Conditions for the existence of planning horizons. Mathematics of Operations Research, 9(3), 391–401. Zabinsky, Z.B. & Smith, R. L. (1992). Pure Adaptive Search in Global Optimization, Mathematical programming 53 (1-3), 323–338. Bélisle, J. P., Romeijn, H. E., & Smith, R. L. (1993). Hit-and-run algorithms for generating multivariate distributions. Mathematics of Operations Research, 18(2), 255–266. Lambert, T. J., Epelman, M. A., & Smith, R. L. (2005). A Fictitious Play Approach to Large-Scale Optimization. Operations Research 53(3), 477–489. References University of Michigan faculty American operations researchers Living people Year of birth missing (living people)