Coalition Formation for Task Allocation Using Multiple Distance Metrics (Student Abstract)

Authors

  • Tuhin Kumar Biswas National Institute of Technology Durgapur, West Bengal, India
  • Avisek Gupta TCG CREST, Kolkata, West Bengal, India
  • Narayan Changder TCG CREST, Kolkata, West Bengal, India
  • Redha Taguelmimt LIRIS, Lyon 1 University, Lyon, France
  • Samir Aknine LIRIS, Lyon 1 University, Lyon, France
  • Samiran Chattopadhyay Techno India University, West Bengal, India
  • Animesh Dutta National Institute of Technology Durgapur, West Bengal, India

DOI:

https://doi.org/10.1609/aaai.v38i21.30421

Keywords:

Coalition Formation, Task Allocation, Distance Metrics

Abstract

Simultaneous Coalition Structure Generation and Assignment (SCSGA) is an important research problem in multi-agent systems. Given n agents and m tasks, the aim of SCSGA is to form m disjoint coalitions of n agents such that between the coalitions and tasks there is a one-to-one mapping, which ensures each coalition is capable of accomplishing the assigned task. SCSGA with Multi-dimensional Features (SCSGA-MF) extends the problem by introducing a d-dimensional vector for each agent and task. We propose a heuristic algorithm called Multiple Distance Metric (MDM) approach to solve SCSGA-MF. Experimental results confirm that MDM produces near optimal solutions, while being feasible for large-scale inputs within a reasonable time frame.

Published

2024-03-24

How to Cite

Biswas, T. K., Gupta, A., Changder, N., Taguelmimt, R., Aknine, S., Chattopadhyay, S., & Dutta, A. (2024). Coalition Formation for Task Allocation Using Multiple Distance Metrics (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23443-23444. https://doi.org/10.1609/aaai.v38i21.30421