3 papers
cs.MA2026
Towards Information-Optimized Multi-Agent Path Finding: A Hybrid Framework with Reduced Inter-Agent Information Sharing
Bharath Muppasani, Ritirupa Dey, Biplav Srivastava +1
Multi-agent pathfinding (MAPF) remains a critical problem in robotics and autonomous systems, where agents must navigate shared spaces efficiently while avoiding conflicts. Traditi…
cs.LG2026
Mitigating Task-Order Sensitivity and Forgetting via Hierarchical Second-Order Consolidation
Protik Nag, Krishnan Raghavan, Vignesh Narayanan
We introduce , a framework that couples fast local adaptation with conservative, second-order global consolidat…
cs.LG2026
Multi-Objective Multi-Fidelity Bayesian Optimization with Causal Priors
Md Abir Hossen, Mohammad Ali Javidian, Vignesh Narayanan +2
Multi-fidelity Bayesian optimization (MFBO) accelerates the search for the global optimum of black-box functions by integrating inexpensive, low-fidelity approximations. The centra…