Abstract. We study the problem of predictive data mining in the competitive multi-agent setting, in which each agent is assumed to have some partial knowledge needed for correctly ...
We present a method for learning a human understandable, executable model of an agent's behavior using observations of its interaction with the environment. By executable we ...
Andrew Guillory, Hai Nguyen, Tucker R. Balch, Char...
This paper defines an approach to simulation of natural systems, inspired by complex systems theory. A complex natural system is modeled as a multi-agent simulation system, agents...
Reasoning about agents that we observe in the world is challenging. Our available information is often limited to observations of the agent’s external behavior in the past and p...
H. Van Dyke Parunak, Sven Brueckner, Robert S. Mat...
Abstract. This paper will discuss the internal architecture for an agent framework called DECAF (Distributed Environment Centered Agent Framework). DECAF is a software toolkit for ...