9 citations · 40 across the 14 of their papers we have counts for
6 papers · 1 filter
Learning to Infer Belief Embedded Communication
Guo Ye, Han Liu, Biswa Sengupta
In multi-agent collaboration problems with communication, an agent's ability to encode their intention and interpret other agents' strategies is critical for planning their future…
Switch Trajectory Transformer with Distributional Value Approximation for Multi-Task Reinforcement Learning
Qinjie Lin, Han Liu, Biswa Sengupta
We propose SwitchTT, a multi-task extension to Trajectory Transformer but enhanced with two striking features: (i) exploiting a sparsely activated model to reduce computation cost…
The Multi-Agent Pickup and Delivery Problem: MAPF, MARL and Its Warehouse Applications
Tim Tsz-Kit Lau, Biswa Sengupta
We study two state-of-the-art solutions to the multi-agent pickup and delivery (MAPD) problem based on different principles -- multi-agent path-finding (MAPF) and multi-agent reinf…
Reinforcement Learning for Location-Aware Scheduling
Stelios Stavroulakis, Biswa Sengupta
Recent techniques in dynamical scheduling and resource management have found applications in warehouse environments due to their ability to organize and prioritize tasks in a highe…
Learning to Ground Decentralized Multi-Agent Communication with Contrastive Learning
Yat Long Lo, Biswa Sengupta
For communication to happen successfully, a common language is required between agents to understand information communicated by one another. Inducing the emergence of a common lan…
Hierarchically Structured Scheduling and Execution of Tasks in a Multi-Agent Environment
Diogo S. Carvalho, Biswa Sengupta
In a warehouse environment, tasks appear dynamically. Consequently, a task management system that matches them with the workforce too early (e.g., weeks in advance) is necessarily…