We consider the problem of learning to attain multiple goals in a dynamic environment, which is initially unknown. In addition, the environment may contain arbitrarily varying ele...
Two distinct learning mechanisms are considered for a population of agents who engage in decentralized search for the common optimum. An agent may choose to learn via innovation (...
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...