Erkin's work focuses on understanding how multiple agents search for the same peaks on a common fitness landscape, or Competitive MultiAgent Search (CMAS). This problem is motivated by innovation search in the real world, i.e. how high-tech companies search for new products. Erkin simulates these processes in NK landscapes, uses evolutionary computation to discover optimal strategies, and verifies the discoveries using human subject data. He is currently trying to finish up his dissertation writing while working full-time at Google, Inc.
erkin [at] cs utexas edu