TAILIEUCHUNG - Báo cáo khoa học: "Plot Induction and Evolutionary Search for Story Generation"

In this paper we develop a story generator that leverages knowledge inherent in corpora without requiring extensive manual involvement. A key feature in our approach is the reliance on a story planner which we acquire automatically by recording events, their participants, and their precedence relationships in a training corpus. | Plot Induction and Evolutionary Search for Story Generation Neil McIntyre and Mirella Lapata School of Informatics University of Edinburgh 10 Crichton Street Edinburgh Eh8 9AB uK mlap@ Abstract In this paper we develop a story generator that leverages knowledge inherent in corpora without requiring extensive manual involvement. A key feature in our approach is the reliance on a story planner which we acquire automatically by recording events their participants and their precedence relationships in a training corpus. Contrary to previous work our system does not follow a generate-and-rank architecture. Instead we employ evolutionary search techniques to explore the space of possible stories which we argue are well suited to the story generation task. Experiments on generating simple children s stories show that our system outperforms previous data-driven approaches. 1 Introduction Computer story generation has met with fascination since the early days of artificial intelligence. Indeed over the years several generators have been developed capable of creating stories that resemble human output. To name only a few Tale-Spin Meehan 1977 generates stories through problem solving Minstrel Turner 1992 relies on an episodic memory scheme essentially a repository of previous hand-coded stories to solve the problems in the current story and Makebelieve Liu and Singh 2002 uses commonsense knowledge to generate short stories from an initial seed story supplied by the user . A large body of more recent work views story generation as a form of agent-based planning Swartjes and Theune 2008 Pizzi et al. 2007 . The agents act as characters with a list of goals. They form plans of action and try to fulfill them. Interesting stories emerge as plans interact and cause failures and possible replanning. The broader appeal of computational story generation lies in its application potential. Examples include the entertainment industry and the .

TỪ KHÓA LIÊN QUAN
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.