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AUSAI
2003
Springer
15 years 9 months ago
Learning Action Selection Network of Intelligent Agent
Behavior-based artificial intelligent system is to derive the complicated behaviors by selecting appropriate one from a set of basic behaviors. Many robot systems have used behavi...
Eun-Kyung Yun, Sung-Bae Cho
AAMAS
2005
Springer
15 years 3 months ago
Cooperative Multi-Agent Learning: The State of the Art
Cooperative multi-agent systems are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among t...
Liviu Panait, Sean Luke
ACL
1998
15 years 5 months ago
Learning Optimal Dialogue Strategies: A Case Study of a Spoken Dialogue Agent for Email
This paper describes a novel method by which a dialogue agent can learn to choose an optimal dialogue strategy. While it is widely agreed that dialogue strategies should be formul...
Marilyn A. Walker, Jeanne Frommer, Shrikanth Naray...
ATAL
2006
Springer
15 years 7 months ago
Probabilistic policy reuse in a reinforcement learning agent
We contribute Policy Reuse as a technique to improve a reinforcement learning agent with guidance from past learned similar policies. Our method relies on using the past policies ...
Fernando Fernández, Manuela M. Veloso
ICML
2003
IEEE
16 years 4 months ago
Q-Decomposition for Reinforcement Learning Agents
The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and...
Stuart J. Russell, Andrew Zimdars