SOAR: an architecture for general intelligence
Artificial Intelligence
Case-based reasoning
Automated intelligent pilots for combat flight simulation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Flying Together: Modelling Air Mission Teams
Applied Intelligence
Thinking Quickly: Agents for Modeling Air Warfare
AI '98 Selected papers from the 11th Australian Joint Conference on Artificial Intelligence on Advanced Topics in Artificial Intelligence
A Formal Specification of dMARS
ATAL '97 Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages
A case study in model selection for policy engineering: simulating maritime customs
AAMAS'11 Proceedings of the 10th international conference on Advanced Agent Technology
| Hi-index | 0.00 |
We are exploring the enhancement of models of agent behaviour with more "human-like" decision making strategies than are presently available. Our motivation is to build multi-agent based simulations of human societies that would exhibit more realistic simulation behaviours. This in turn will allow researchers to study more complex issues regarding individual and organisational performance than is possible with present systems. Drawing on studies into naturalistic decision making, which looks at people's decision making in their natural environments, we propose ways of integrating a recognition-primed decision making approach with the popular BDI agent architecture, and report on preliminary empirical studies.