Erkin's work focused 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 simulated these processes in NK landscapes, used evolutionary computation to discover optimal strategies, and verified the discoveries using human subject data. After graduation (and even before it) he went to work at Google, Inc.
erkin [at] cs utexas edu