We consider a multiagent system whose task is to aid componentcentered design by collaborative designers in a supply chain. In the earlier work, collaborative design networks are ...
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
Developing multi-agent simulations seems to be rather straight forward, as active entities in the original correspond to active agents in the model. Thus plausible behaviors can be...
Service matchmaking is the process of finding suitable services given by the providers for the service requests of consumers. Previous approaches to service matchmaking is mostly ...
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...