Technical Note: \cal Q-Learning
Machine Learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Validation, verification, and testing techniques throughout the life cycle of a simulation study
WSC '94 Proceedings of the 26th conference on Winter simulation
Introduction to the art and science of simulation
Proceedings of the 30th conference on Winter simulation
The Gaia Methodology for Agent-Oriented Analysis and Design
Autonomous Agents and Multi-Agent Systems
Simulation for the Social Scientist
Simulation for the Social Scientist
Rule Extraction from Recurrent Neural Networks: A Taxonomy and Review
Neural Computation
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Generalized model learning for reinforcement learning in factored domains
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Prometheus: a methodology for developing intelligent agents
AOSE'02 Proceedings of the 3rd international conference on Agent-oriented software engineering III
ADELFE: a methodology for adaptive multi-agent systems engineering
ESAW'02 Proceedings of the 3rd international conference on Engineering societies in the agents world III
Introducing pattern reuse in the design of multi-agent systems
NODe'02 Proceedings of the NODe 2002 agent-related conference on Agent technologies, infrastructures, tools, and applications for E-services
Multi-agent based simulation: where are the agents?
MABS'02 Proceedings of the 3rd international conference on Multi-agent-based simulation II
Towards pattern-oriented design of agent-based simulation models
MATES'09 Proceedings of the 7th German conference on Multiagent system technologies
Evaluation of techniques for a learning-driven modeling methodology in multiagent simulation
MATES'10 Proceedings of the 8th German conference on Multiagent system technologies
Evolution for modeling: a genetic programming framework for sesam
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
IODA: an interaction-oriented approach for multi-agent based simulations
Autonomous Agents and Multi-Agent Systems
Behavior modeling from learning agents: sensitivity to objective function details
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
PROGRAMMING AGENT BEHAVIOR BY LEARNING IN SIMULATION MODELS
Applied Artificial Intelligence - Eighth European Workshop on Multi-Agent Systems EUMAS 2010
Learning agent models in SeSAm
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
| Hi-index | 0.00 |
The question of what is the best way to develop an agent-based simulation model becomes more important as this paradigm is more and more used. Clearly, general model development processes can be used, but these do not solve the major problems of actually deciding about the agents' structure and behavior. In this contribution we introduce the MABLe methodology for analyzing and designing agent simulation models that relies on adaptive agents, where the agent helps the modeler by proposing a suitable behavior program. We test our methodology in a pedestrian evacuation scenario. Results demonstrate the agents can learn and report back to the modeler a behavior that is interestingly better than a hand-made model.