We describe an approach based upon software process technology to on-the-fly monitoring, redeployment, reconfiguration, and in general dynamic adaptation of distributed software ap...
Affective and human-centered computing have attracted a lot of attention during the past years, mainly due to the abundance of devices and environments able to exploit multimodal i...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Complexity of near future and even nowadays applications is exponentially increasing. In order to tackle the design of such complex systems, being able to engineer self-organising ...
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...