In many scenarios of interest, agents may only have access to partial information about an
unknown model or target vector. Each agent may be sensing only a subset of the entries of a …

Effective coordination of agents actions in partially-observable domains is a major challenge
of multi-agent systems research. To address this, many researchers have developed …

Effective coordination of agents' actions in partially-observable domains is a major
challenge of multi-agent systems research. To address this, many researchers have …

In distributed inference, cooperation among networked agents can be exploited to enhance
the performance of each individual agent. In this paper, we consider signal classification …

In a network, each agent communicates with its neighbors. All the agents have initial
observations, and they update their beliefs with the average of the beliefs in their …

This work develops an effective distributed algorithm for the solution of stochastic
optimization problems that involve partial coupling among both local constraints and local …

We study a multi-agent partially observable environment in which autonomous agents aim to
coordinate their actions, while also learning the parameters of the unknown environment …

Information exchange in multi-agent systems improves the cooperation among agents,
especially in partially observable settings. In the real world, communication is often carried …

Multiagent learning provides a promising paradigm to study how autonomous agents learn
to achieve coordinated behavior in multiagent systems. In multiagent learning, the …

A network of agents attempt to learn some unknown state of the world drawn by nature from
a finite set. Agents observe private signals conditioned on the true state, and form beliefs …