A Smarter Way to Scale Multi-Agent Pathfinding
18 Feb 2026
A new LayeredMAPF framework decomposes multi-agent pathfinding into smaller subproblems, reducing complexity while preserving solvability.
Researchers Compare CBS, LNS, PBS, and PIBT in the Race to Speed Up Multi-Agent Pathfinding
18 Feb 2026
Survey of MAPF algorithms—from CBS and LNS to PBS and LaCAM—focused on reducing runtime while balancing optimality and scalability.
This New Decomposition Framework Makes Multi-Agent Pathfinding More Scalable
18 Feb 2026
A new decomposition framework reduces time and memory costs in multi-agent pathfinding without sacrificing solvability.
Beyond TPC-H: Scaling IA2 for Real-World Database Optimization
10 Jan 2026
IA2 sets a new standard for database optimization using the TD3-TD-SWAR model, offering superior efficiency and unseen workload generalization.
Adaptive Action Pruning: Scaling Index Selection for Unseen Workloads
10 Jan 2026
IA2 revolutionizes index selection with rapid training, reducing SQL runtime by 61% via adaptive action pruning and workload modeling
Beyond SWIRL: Scalable Database Indexing for Dynamic Workloads
10 Jan 2026
IA2 outperforms SWIRL and other methods by 15-20%, achieving a 61% runtime improvement through storage-aware RL and rapid training efficiency.
Adaptive Action Pruning: Scaling Databases with Intelligent Action Masking
9 Jan 2026
IA2 outpaces SWIRL and Lan et al. in training efficiency using TD3-TD-SWAR and adaptive action masking for faster SQL index selection.
PostgreSQL & HypoPG: The Experimental Foundation of IA2 Index Selection
7 Jan 2026
IA2 demonstrates significant database optimization on TPC-H benchmarks using PostgreSQL and HypoPG, achieving superior end-to-end runtime gains.
Beyond Preprocessing: Sequential Indexing and Temporal Consistency in IA2
7 Jan 2026
IA2 uses the TD3-TD-SWAR algorithm to adaptively mask irrelevant indexes, ensuring robust performance optimization for both familiar and unseen workloads.