Amit Sarker

Agent Society

Amit Sarker

Ph.D. Candidate · UMass Amherst

Pixel-art portrait of Amit Sarker

I am a Ph.D. candidate in Computer Science at the University of Massachusetts Amherst, where I work with Prof. Shlomo Zilberstein in the Resource-Bounded Reasoning Lab.

My research focuses on agents built on large language models (LLMs) that negotiate, coordinate, and share resources with one another. Their goals often only partly align, so each agent must decide what to say, whom to believe, and when to cooperate. I'm interested in the following research areas:

  • Trust and Reputation in Strategic Reasoning: Can agents learn whom to trust from past interactions? How should trust and reputation change what they propose, accept, and say?
  • Social Agents and Strategic Communication: How do LLM agents negotiate, persuade, and build relationships when their goals only partly align? What social reasoning capabilities are required for effective collaboration with humans and other agents?
  • Emergent Behavior of Multi-Agent Systems: What behaviors, such as collusion or favors that bypass the rules, emerge when agents interact over many rounds? When do these behaviors help a group, and when do they cause harm?

Previously, I studied how visualization supports differential privacy in practice. Before my Ph.D., I worked on distributed constraint optimization with Prof. Md Mosaddek Khan at the Cognitive Agents and Interaction Lab (CAIL). I also worked as a software engineer at TigerIT Bangladesh. I received my B.Sc. in Computer Science and Engineering from the University of Dhaka.

Publications

* indicates equal contribution

Five agents negotiate over five issues while one covert adversary rejects proposals; each agent keeps trust scores for the othersarXiv 2026

Knowing Whom to Trust is not Enough: The Trust–Agreement Gap in Repeated Multi-Party LLM Negotiation

Multi-Agent SystemsTrust & Negotiation

Amit Sarker, Moumita Choudhury, Saaduddin Mahmud, Shlomo Zilberstein

arXiv 2026

Agents spot a hidden adversary within a few games. Yet their trust improves agreement only when they are guided to use it.

paper website
An agent edits a shared file as a favor when the reviewer is away; its teammate's task passes but another team's task failsarXiv 2026

The Helpful Agent Problem: When Emergent Cooperation Among LLM Agents Bypasses Intended Workflows

Multi-Agent SystemsAlignment & Safety

Moumita Choudhury, Amit Sarker, Shlomo Zilberstein

arXiv 2026

When review is unavailable, agents often do favors for one another that skip it. Many favors succeed locally but break other teams' work.

paper website
Five LLM agents around a negotiation table: the covert adversary has been detected and trust among the honest parties is high, yet one honest party holds out and the game ends with no dealSocialAgent@NeurIPS 2026

The Benefits and Limits of Trust Models in Repeated Multi-Party Negotiation with LLM Agents

Multi-Agent SystemsTrust & Negotiation

Amit Sarker, Moumita Choudhury, Saaduddin Mahmud, Shlomo Zilberstein

NeurIPS 2026 Workshop on Large Language Models for Social Reasoning and Simulation (SocialAgent)

paper
Five stages of a differential privacy deployment and the people involved at each stageTVCG 2024

Illuminating the Landscape of Differential Privacy: An Interview Study on the Use of Visualization in Real-World Deployments

Privacy & Visualization

Liudas Panavas*, Amit Sarker*, Sara Di Bartolomeo, Ali Sarvghad, Cody Dunne, Narges Mahyar

IEEE TVCG 2024

paper supplement
Constraint graph of four agents and their cost functionsAAMAS 2021

A Local Search Based Approach to Solve Continuous DCOPs

Multi-Agent SystemsOptimization

Amit Sarker, Moumita Choudhury, Md Mosaddek Khan

AAMAS 2021

paper code slides
  • A Particle Swarm Inspired Approach for Continuous Distributed Constraint Optimization Problems
    Multi-Agent SystemsOptimization
    Moumita Choudhury, Amit Sarker, Samin Yaser, Md Maruf Al Alif Khan, William Yeoh, Md Mosaddek Khan
    EAAI 2023
    paper code
  • C-CoCoA: A Continuous Cooperative Constraint Approximation Algorithm to Solve Functional DCOPs
    Multi-Agent SystemsOptimization
    Amit Sarker, Abdullahil Baki Arif, Moumita Choudhury, Md Mosaddek Khan
    AAMAS 2020 (extended abstract)
    paper

News

2026
2025
  • MayI passed the comprehensive exam and advanced to Ph.D. candidacy!
2024

Honors & Service

Honors

  • Dr. Phil Bernstein Graduate Scholarship in Computer ScienceUMass Amherst2025
  • James Kurose Scholarship in Computer ScienceUMass Amherst2023
  • Conference ScholarshipAAMAS 2021 and AAMAS 20202020–21
  • 1st Runner-Up, Code Samurai HackathonFinding efficient transportation routes in Dhaka city2019

Service

  • ReviewerAAAI 20262026
  • Program CommitteeAIES 20252025
  • Student VolunteerIEEE VIS 20232023
  • Student VolunteerAAMAS 2021 and AAMAS 20202020–21

Teaching

  • Teaching Assistant, COMPSCI 325: Introduction to Human-Computer InteractionMentored 12 student teams through their final projectsFall 2024
  • Teaching Assistant, CICS 110: Foundations of ProgrammingRan weekly Python labs for over 100 studentsFall 2023