.png){kind=icon}
.png){kind=icon}
Return
Agendas for multi-agent learning
.png){kind=icon}
OA
AI
DOI：10.1016/j.artint.2006.12.006.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Shoham et al. identify several important agendas which can help direct research in multi-agent learning. We propose two additional agendas-called modelling and design - which cover the problems we need to consider before our agents can start learning. We then consider research goals for modelling, design, and learning, and identify the problem of finding learning algorithms that guarantee convergence to Pareto-dominant equilibria against a wide range of opponents. Finally, we conclude with an example: starting from an informally-specified multi-agent learning problem, we illustrate how one might formalize and solve it by stepping through the tasks of modelling, design, and learning. (c) 2007 Elsevier B.V. All rights reserved.
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
13.9
Papers:
6.1K
Citations:
1.9W
Organization
No organization information available