Humor generation is one of the tasks of computational creativity, which can not only make a computer creative and have a personality, but also improve user experiences. This paper explores the generation of Chinese jokes, the main form of humor. In particular, the following task is considered: given the setup of a joke, generate the corresponding punchline that is in line with current natural language generation technologies using one of two approaches. One is based on the encoder-decoder framework and lacks modeling of humor characters. The other is based on generative adversarial networks (GANs), in which four characters (ambiguity, incongruity, phonetic similarity, and universality) are introduced into the reward function to evaluate the generated jokes and supervise the generator. Experimental results show that the GANs approach with joke character rewards obtains promising improvements compared to the encoder-decoder framework, namely, extra six percentage points on the ratio of jokes. While the performance is insufficient, as a first step towards creative language generation, the insights obtained in the exploration will help us in future research.