A scalable approach to trust negotiation is required in Web service environments that have large and dynamic requester populations. We introduce Trust-Serv, a model-driven trust n...
This paper develops a model for exceptions and an approach for incorporating them in commitment protocols among autonomous agents. Modeling and handling exceptions is critical for...
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...