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New dynamic programming approach optimizes multi-agent communication-control

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new dynamic-programming approach to optimize joint communication-control strategies in multi-agent linear systems. This method specifically addresses problems with quadratic costs and partially nested information structures within the decentralized stochastic control framework. The approach yields closed-form Riccati Equations and can also solve decentralized linear-quadratic control problems with output feedback. AI

RANK_REASON The cluster contains an academic paper detailing a new technical approach. [lever_c_demoted from research: ic=1 ai=0.1]

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dynamic programming approach optimizes multi-agent communication-control

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The cluster contains an academic paper detailing a new technical approach. [lever_c_demoted from research: ic=1 ai=0.1]
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COVERAGE [1]

  1. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Kaiqing Zhang ·

    Joint Communication-Control Strategy Optimization with Partially Nested Information Structures: The Linear-Quadratic Case

    In this paper, we formalize a joint communication-control strategy optimization (JCCO) problem in multi-agent linear systems with quadratic costs, under the common-information-based (CIB) framework from decentralized stochastic control. For computational tractability, we focus on…

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