Thisbook deals with analytic treatments of Markov processes. Symmetric Dirichlet forms andtheir associated Markov processes are important and powerful toolsin the theory of Markovprocesses and their applications. The theoryis well studied and used in various fields. In this monograph, we intend togeneralize the theory to non-symmetric and time dependent semi-Dirichlet forms. By this generalization, we can cover the wide class of Markov processes and analytic theory which do not possess the dualMarkov processes. In particular, under the semi-Dirichlet form setting, the stochastic calculus is not well established yet.In this monograph, we intend to give an introduction to such calculus. Furthermore, basic examples different from the symmetric cases are given.Thetext is writtenfor graduate students, but alsoresearchers.weiterlesen