This project is about develop a PPO-style solver for multi-agent continual learning under latent non-stationarity, where decentralized agents act in a sequence of partially observed stochastic games whose hidden modes encode changing tasks, teammate roles, or environment dynamics. The student would extend multi-agent PPO, so that agents can adapt online to the current hidden regime while reducing forgetting on previously encountered regimes. The project would combine algorithm design with controlled theory-facing experiments: starting from two-agent hidden-mode coordination games, then scaling to robot-team or agentic-system benchmarks, and evaluating performance through adaptation speed, team return, individual forgetting, coordination forgetting, and robustness to teammate/environment drift.
Education and Experience Requirements
• The entirety of the appointment must be conducted within the United States.
• Applicants must be:
o Currently enrolled in undergraduate or graduate studies at an accredited institution.
o Graduated from an accredited institution within the past 3 months; or
o Actively enrolled in a graduate program at an accredited institution.
• Must be 18 years or older at the time the appointment begins.
• Must possess a cumulative GPA of 3.0 on a 4.0 scale.
• If accepting an offer, candidates may be required to complete pre-employment drug testing based on appointment length. All students remain subject to applicable drug testing policies.
• Must complete a satisfactory background check.
Job Family
Graduate Thesis AppointmentJob Profile
Graduate ResearchWorker Type
EmployeeTime Type
Full timeScheduled Weekly Hours
40Pay Rate Type
HourlyThe expected hiring range for this position is $19.80-$46.92.Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
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EEO Information
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers for appointments in the student employment category are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.
| Location | Lemont, Illinois |
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