This paper introduces a new model, i.e. state-coupled replicator dynamics, expanding the link between evolutionary game theory and multiagent reinforcement learning to multistate ...
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
Automated agents for electricity markets, social networks, and other distributed networks must repeatedly interact with other intelligent agents, often without observing associate...
Jacob W. Crandall, Asad Ahmed, Michael A. Goodrich
A mobile agent with the task to classify its sensor pattern has to cope with ambiguous information. Active recognition of three-dimensional objects involves the observer in a sear...
The ambitious goal of transfer learning is to accelerate learning on a target task after training on a different, but related, source task. While many past transfer methods have f...