Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
AI Game Programming Wisdom
AI Game Programming Wisdom
Personality Parameters and Programs
Creating Personalities for Synthetic Actors, Towards Autonomous Personality Agents
Characters in Search of an Author: AI-Based Virtual Storytelling
ICVS '01 Proceedings of the International Conference on Virtual Storytelling: Using Virtual Reality Technologies for Storytelling
Cooperative Multi-Agent Learning: The State of the Art
Autonomous Agents and Multi-Agent Systems
Adaptive game AI with dynamic scripting
Machine Learning
Human behavior models for agents in simulators and games: part II: gamebot engineering with PMFserv
Presence: Teleoperators and Virtual Environments
The case for dynamic difficulty adjustment in games
Proceedings of the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology
Flow in games (and everything else)
Communications of the ACM
DEAL: dialogue management in SCXML for believable game characters
Future Play '07 Proceedings of the 2007 conference on Future Play
2APL: a practical agent programming language
Autonomous Agents and Multi-Agent Systems
THESPIAN: An Architecture for Interactive Pedagogical Drama
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
The DEFACTO system: training tool for incident commanders
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
Adaptive Serious Games Using Agent Organizations
Agents for Games and Simulations
Failing believably: toward drama management with autonomous actors in interactive narratives
TIDSE'06 Proceedings of the Third international conference on Technologies for Interactive Digital Storytelling and Entertainment
S-Moise+: a middleware for developing organised multi-agent systems
AAMAS'05 Proceedings of the 2005 international conference on Agents, Norms and Institutions for Regulated Multi-Agent Systems
| Hi-index | 0.00 |
Serious games and other training applications have the requirement that they should be suitable for trainees with different skill levels. Current approaches either use human experts or a completely centralized approach for this adaptation. These centralized approaches become very impractical and will not scale if the complexity of the game increases. Agents can be used in serious game implementations as a means to reduce complexity and increase believability but without some centralized coordination it becomes practically impossible to follow the intended storyline of the game and select suitable difficulties for the trainee. In this paper we show that using agent organizations to coordinate the agents is scalable and allows adaptation in very complex scenarios while making sure the storyline is preserved the right difficulty level for the trainee is preserved.