In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a a new probabilistic planning rule representation to compactly ...
Hanna M. Pasula, Luke S. Zettlemoyer, Leslie Pack ...
We present a generalization of conventional artificial neural networks that allows for a functional equivalence to multi-expert systems. The new model provides an architectural fr...
We present a robust method for time-frequency model estimation. It involves a robust Leclerc's estimator to ensure robustness w.r.t. noise and interferences present in timefr...
Ronan Fablet, Abdessalam Benzinou, Christian Donca...
Though there is a multitude of software modeling tools available, the handling of diagrams, which are an essential way of representation, is still difficult. To overcome these pr...
In multiagent adversarial domains, team agents should adapt to the environment and opponent. We introduce a model representation as part of a planning process for a simulated socce...