A Simulation Method For Virtual Situations Through Seamless Integration Of Independent Events Via Autonomous And Independent Agents

다국어 초록 (Multilingual Abstract)

The extent and depth of the event plan determines the scope of pedagogical experience in situations and consequently the quality of immersive learning based on our simulated world. In contrast to planning in conventional narrative-based systems mainly pursuing dramatic interests, planning in virtual world-based pedagogical systems strive to provide realistic experiences in immersed situations. Instead of story plot comprising predetermined situations, our inter-event planning method aims at simulating diverse situations that each involve multiple events coupled via their associated agents’ conditions and meaningful associations between events occurring in a background world. The specific techniques to realize our planning method include, two-phase planning based on inter-event search and intra-event decomposition (down to the animated action level); autonomous and independent agents to behave proactively with their own belief and planning capability; full-blown background world to be used as the comprehensive stage for all events to occur in; coupling events via realistic association types including deontic associations as well as conventional causality; separation of agents from event roles; temporal scheduling; and parallel and concurrent event progression mechanism. Combining all these techniques, diverse exogenous events can be derived and seamlessly (i.e., semantically meaningfully) integrated with the original event to form a wide scope of situations providing chances of abundant pedagogical experiences. For effective implementation of plan execution, we devise an execution scheme based on multiple priority queues, particularly to realize concurrent progression of many simultaneous events to simulate its corresponding reality. Specific execution mechanisms include modeling an action in terms of its component motions, adjustability of priority for agent across different events, and concurrent and parallel execution method for multiple actions and its expansion for multiple events.

참고문헌 (Reference)

1 W. Swartout, "Toward the Holodeck: Integrating graphics, sound, character and story" 2001

2 K. Hartsook, "Toward supporting stories with procedurally generated game worlds" 2011

3 M. Riedl, "The Importance of Narrative as an Affective Instructional Strategy, Design Recommendations for Adaptive ITS : Adaptive Instructional Strategies, vol. 2" 2014

4 W. Johnson, "The DARWARS Tactical Language Training System" 2004

5 F. Charles, "Planning formalisms and authoring in interactive storytelling" 3 : 216-225, 2003

6 A. Shoulson, "Parameterizing Behavior Trees, In Motion In Games" Springer 144-155, 2011

7 R. Hodhod, "Innovative integrated architecture for educational games: challenges and merits, Transactions on edutainment v, vol. 5" Springer Berlin Heidelberg 1-34, 2011

8 박종희, "Implementation of an Agent-centric Planning of Complex Events as Objects of Pedagogical Experiences in Virtual World" 한국콘텐츠학회 12 (12): 25-43, 2016

9 K. Erol, "Hierarchical Task Network Planning: Formalization, Analysis, and Implementation" Univ. of Maryland 1996

10 L. Amaral, "From recording linguistic competence to supporting inferences about language acquisition in context" 21 (21): 323-338, 2008

11 Mei Si, "Evaluating Directorial Control in a Character-Centric Interactive Narrative Framework" 1289-1296, 2010

12 M. Cavazza, "Emergent situations in interactive storytelling" 2002

13 J. Thomas, "Becoming Scientists: Employing Adaptive Interactive Narrative to Guide Discovery Learning" 2007

14 A. Zook, "Automated scenario generation: toward tailored and optimized military training in virtual environments" ACM 2012

15 J. Porteous, "Applying planning to interactive storytelling: Narrative control using state constraints" 1 (1): 2010

16 J. Choi, "An Effective implementation of agent's complex actions by reusing primitive motions" 2014

17 M. Kapadia, "A behavior-authoring framework for multiactor simulations" 31 (31): 44-55, 2011