Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
This paper describes a probabilistic framework to estimate the shape and position of multiple fish in a school. We model the fish shape as an ellipsoid with a curvature coefficient...
Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of...
s the abstracted cognitive behaviours of the controllers and their tools in performingw the traffic management task. Taken together, the models provide a statement of worksystem pe...
Abstract. In this paper we address the problem of granting the correctness of Grid computations. We introduce a Grid Integrity Validation Scheme (GIVS) that may reveal the presence...