This paper describes our work constructing a generalized framework for modeling multi agent interactions in education-related applications. Historically, interactive learning syst...
Reward shaping is a well-known technique applied to help reinforcement-learning agents converge more quickly to nearoptimal behavior. In this paper, we introduce social reward sha...
Monica Babes, Enrique Munoz de Cote, Michael L. Li...
Embedded systems consisting of collaborating agents capable of interacting with their environment are becoming ubiquitous. It is crucial for these systems to be able to adapt to t...
This paper is concerned with synthetic agents interacting with virtual environments, called animated creatures. The animated creatures are articulated graphical gures that are eq...
—This paper describes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The artificial market, na...