99 search results - page 8 / 20 » A Reinforcement Learning Approach for Multiagent Navigation |
ROBOCUP
2007
Springer
15 years 4 months ago
2007
Springer
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
The purpose of this paper is three-fold. First, we formalize and study a problem of learning probabilistic concepts in the recently proposed KWIK framework. We give details of an ...
ROBOCUP
2009
Springer
15 years 4 months ago
2009
Springer
As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
AGENTS
1999
Springer
15 years 2 months ago
1999
Springer
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
ESAW
2008
Springer
14 years 11 months ago
2008
Springer
Reactive multi-agent systems present global behaviours uneasily linked to their local dynamics. When it comes to controlling such a system, usual analytical tools are difficult to ...