activity
19992025
most citedImproving Performance of heavily loaded agents

4 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2025

Strategic Communication under Threat: Learning Information Trade-offs in Pursuit-Evasion Games

Valerio La Gatta, Dolev Mutzari, Sarit Kraus +1

Adversarial environments require agents to navigate a key strategic trade-off: acquiring information enhances situational awareness, but may simultaneously expose them to threats.…

cs.RO2025

Multi-Object Active Search and Tracking by Multiple Agents in Untrusted, Dynamically Changing Environments

Mingi Jeong, Cristian Molinaro, Tonmoay Deb +5

This paper addresses the problem of both actively searching and tracking multiple unknown dynamic objects in a known environment with multiple cooperative autonomous agents with pa…

cs.CL2024★ 4 cited

Higher Layers Need More LoRA Experts

Chongyang Gao, Kezhen Chen, Jinmeng Rao +7

Parameter-efficient tuning (PEFT) techniques like low-rank adaptation (LoRA) offer training efficiency on Large Language Models, but their impact on model performance remains limit…

cs.MA2000★ 4 cited

Improving Performance of heavily loaded agents

Fatma Ozcan, VS Subrahmanian, Juergen Dix

With the increase in agent-based applications, there are now agent systems that support \emph{concurrent} client accesses. The ability to process large volumes of simultaneous requ…

cs.AI1999

Probabilistic Agent Programs

Juergen Dix, Mirco Nanni, VS Subrahmanian

Agents are small programs that autonomously take actions based on changes in their environment or ``state.'' Over the last few years, there have been an increasing number of effort…