Adaptive Multi-Agent Programming in GTGolog

被引：0
|
作者：
Finzi, Alberto [1 ,2 ]
Lukasiewicz, Thomas [1 ,2 ]
机构：
[1] TU Wien, Inst Informat Syst, Favoritenstr 9-11, A-1040 Vienna, Austria
[2] Univ Roma La Sapienza, DIS, I-00198 Rome, Italy
来源：
ECAI 2006, PROCEEDINGS | 2006年 / 141卷
基金：
奥地利科学基金会;
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present a novel approach to adaptive multi-agent programming, which is based on an integration of the agent programming language GTGolog with adaptive dynamic programming techniques. GTGolog combines explicit agent programming in Golog with game-theoretic multi-agent planning in stochastic games. In GTGolog, the transition probabilities and reward values of the domain must be provided with the model. The adaptive generalization of GTGolog proposed here is directed towards letting the agents themselves explore and adapt these data. We use high-level programs for the generation of both abstract states and optimal policies.
引用
收藏
页码：753 / +
页数：2
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