PhD Dissertation Defense by AGRAWAL Pritee | Proactive and Reactive Resource/Task Allocation for Agent Teams in Uncertain Environments

Proactive and Reactive Resource/Task Allocation for Agent Teams in Uncertain Environments

About The Talk

Synergistic interactions between task/resource allocation and multi-agent coordinated planning/assignment exist in many problem domains such as transportation and logistics, disaster rescue, security patrolling, power distribution networks etc. These domains often feature dynamic environments where allocations of tasks/resources may have complex dependencies and agents may leave the team due to unforeseen conditions (e.g., emergency, accident or violation, damage to agent, reconfiguration of environment).

This dissertation seeks to provide computationally efficient and scalable mechanisms for solving task/resource constrained multi-agent planning/assignment problems with abilities to handle dependencies between tasks/resources, non dedication in agent teams and reconfiguration of the environment due to an external event. To that end, we provide generic models to handle task/resource constrained multi-agent planning/assignment for dedicated and non-dedicated agent teams. We also design scalable proactive and reactive algorithms that provide provable quality-bounds. The proactive approaches mainly exploit decomposability to solve independent agent planning/assignment problems and provide posterior quality guarantees while the reactive approaches are highly efficient and provide very quick solutions but without quality guarantees. Finally, the proposed solution approaches are shown to be highly scalable and more efficient in comparison with existing solutions on the real-world and synthetic benchmarks from literature.

Speaker Biography

AGRAWAL Pritee is a PhD candidate in School of Information Systems, SMU specialising in Intelligent Systems & Optimization under the supervision of Associate Professor Pradeep Varakantham. Her current research focuses on designing algorithms for large scale optimisation problems in urban environments and solving task/resource allocation for multi-agent systems.