The paper describes the architecture of Brown University’s agent, Botticelli, a finalist in the 2003 Trading Agent Competition in Supply Chain Management (TAC SCM). In TAC SCM,...
Michael Benisch, Amy R. Greenwald, Ioanna Grypari,...
The general aim of our work is to provide tools, methods and models to adaptive multi-agent systems designers. These systems consist in several interacting agents and have to optim...
In this paper, we describe a cooperative transportation to a target position with two humanoid robots and introduce a machine learning approach to solving the problem. The difficul...
Recent research has shown that annotations are useful for representing access restrictions to the axioms of an ontology and their implicit consequences. Previous work focused on as...
Reinforcement learning techniques are increasingly being used to solve di cult problems in control and combinatorial optimization with promising results. Implicit imitation can acc...