45 search results - page 8 / 9 » Stigmergy in Multi Agent Reinforcement Learning |
SASO
2009
IEEE
14 years 1 days ago
2009
IEEE
—Large-scale agent-based systems are required to self-optimize towards multiple, potentially conflicting, policies of varying spatial and temporal scope. As a result, not all ag...
ATAL
2004
Springer
13 years 10 months ago
2004
Springer
Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS’s). First we review one motivation of PD theory, as the information-theoretic extens...
PPSN
2004
Springer
13 years 10 months ago
2004
Springer
In Multi-Agent learning, agents must learn to select actions that maximize their utility given the action choices of the other agents. Cooperative Coevolution offers a way to evol...
TSMC
2008
13 years 5 months ago
2008
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
IROS
2008
IEEE
13 years 11 months ago
2008
IEEE
—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...