ABSTRACT
In order to act rationally, an agent must track the state of the environment over time. In the presence of other agents who themselves act, observe, and update their beliefs the agent must track not only the physical state but also the possible states of others. This is because others' actions may affect the evolution of the physical state and the agent's payoffs. One approach is to generalize the Bayes filter to multiagent settings, in which an agent tracks the evolution of the interactive state [2]. In practice, the estimation may be carried out using the interactive PF (I-PF) [2] that generalizes the PF to the multiagent setting.
- P. Doshi. Improved state estimation in multiagent settings with continuous or large discrete state spaces. In AAAI, pages 712--717, 2007. Google ScholarDigital Library
- P. Doshi and P. J. Gmytrasiewicz. Approximating state estimation in multiagent settings using particle filters. In AAMAS, pages 320--327, 2005. Google ScholarDigital Library
- E. Snelson and Z. Ghahramani. Compact approximations to bayesian predictive distributions. In ICML, pages 840--847, 2005. Google ScholarDigital Library
Index Terms
- Compact approximations of mixture distributions for state estimation in multiagent settings
Recommendations
Approximate state estimation in multiagent settings with continuous or large discrete state spaces
AAMAS '07: Proceedings of the 6th international joint conference on Autonomous agents and multiagent systemsWe present a new method for carrying out state estimation in multi-agent settings that are characterized by continuous or large discrete state spaces. State estimation in multiagent settings involves updating an agent's belief over the physical states ...
Approximating state estimation in multiagent settings using particle filters
AAMAS '05: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systemsState estimation consists of updating an agent's belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalized using the Bayes filter. Exact estimation can be performed in simple cases, ...
Improved state estimation in multiagent settings with continuous or large discrete state spaces
AAAI'07: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1State estimation in multiagent settings involves updating an agent's belief over the physical states and the space of other agents' models. Performance of the previous approach to state estimation, the interactive particle filter, degrades with large ...
Comments