English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Being able to predict the mental states of others is a key factor toeffective social interaction. It is also crucial for distributed multi-agentsystems, where agents are required to communicate and cooperate. In this paper,we introduce such an important social-cognitive skill, i.e. Theory of Mind(ToM), to build socially intelligent agents who are able to communicate andcooperate effectively to accomplish challenging tasks. With ToM, each agent iscapable of inferring the mental states and intentions of others according toits (local) observation. Based on the inferred states, the agents decide "when"and with "whom" to share their intentions. With the information observed,inferred, and received, the agents decide their sub-goals and reach a consensusamong the team. In the end, the low-level executors independently takeprimitive actions to accomplish the sub-goals. We demonstrate the idea in twotypical target-oriented multi-agent tasks: cooperative navigation andmulti-sensor target coverage. The experiments show that the proposed model notonly outperforms the state-of-the-art methods on reward and communicationefficiency, but also shows good generalization across different scales of theenvironment.

ToM2C: Target-oriented Multi-agent Communication and Cooperation with Theory of Mind