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We consider a multi-agent linear quadratic optimal control problem. Due to communication constraints, the agents are required to quantize their local state measurements before communicating them to the rest of the team, thus resulting in a decentralized information structure. The optimal controllers are to be synthesized under this decentralized and quantized information structure. The agents are given a set of quantizers with varying quantization resolutions—higher resolution incurs higher communication cost and vice versa. The team must optimally select the quantizer to prioritize agents with ‘highquality’ information for optimizing the control performance under communication constraints. We show that there exist a sepatation between the optimal solution to the control problem and the choice of the optimal quantizer. We show that the optimal controllers are linear and the optimal selection of the quantizers can be determined by solving a linear program.
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This content will become publicly available on February 1, 2026
Emergence of multiple foraging strategies under competition
Foraging strategies are shaped by interactions with the environment, and evolve under metabolic constraints. Optimal strategies for isolated and competing organisms have been studied extensively in the absence of evolution. Much less is understood about how metabolic constraints shape the evolution of an organism’s ability to detect and reach food. To address this question, we introduce a minimal agent-based model of the coevolution of two phenotypic attributes critical for successful foraging in crowded environments: movement speed and perceptual acuity. Under competition higher speed and acuity lead to better foraging success, but at higher metabolic cost. We derive the optimal foraging strategy for a single agent, and show that this strategy is no longer optimal for foragers in a group. We show that mutation and selection can lead to the coexistence of two strategies: A metabolically costly strategy with high acuity and velocity, and a metabolically cheap strategy. Generally, in evolving populations speed and acuity co-vary. Therefore, even under metabolic constraints, trade-offs between metabolically expensive traits are not guaranteed.
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- Award ID(s):
- 2207647
- PAR ID:
- 10634744
- Editor(s):
- NA
- Publisher / Repository:
- Mathematical Biosciences
- Date Published:
- Journal Name:
- Mathematical Biosciences
- Volume:
- 380
- Issue:
- C
- ISSN:
- 0025-5564
- Page Range / eLocation ID:
- 109377
- Subject(s) / Keyword(s):
- foraging, evolution
- Format(s):
- Medium: X Size: N/A Other: N/A
- Size(s):
- N/A
- Sponsoring Org:
- National Science Foundation
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