Intelligent Machines & Sociotechnical Systems Lab

At the iMaSS lab, we conduct fundamental research on the analysis and design of complex networks, which consist of a large number of intelligent decisions makers. In our research, we deal with scenarios in which the intelligent decision makers can be machines like robots, or humans, or a combination of both.

  • In multi-robot systems, our focus is on designing real-time distributed algorithms to achieve some desired objective with performance guarantees.

  • In social systems comprising human decision makers, our focus is on developing and analyzing various behavior based models for human decision making and their impacts at the societal level.

  • In sociotechnical systems that involve both intelligent machines and human decision makers, we are interested in understanding how humans and machines both work together and influence the behavior of each other.

Real-time Distributed Optimization for Multi-Robot Systems

In multi-robot systems, a group of mobile robots are assigned a certain task like area surveillance and the robots have to accomplish the assigned task while working collaboratively as a team. We develop distributed algorithms that enable the robots to accomplish the assigned tasks in the absence of any centralized supervision. In these distributed algorithms, the robots have to make decisions based on their local information from on-board sensors and the information they receive from other robots via communication. Our objective is to design distributed algorithms that can evaluate all this information and compute feasible/optimal actions in real-time. Real-time algorithms are critical for the safe and reliable operation of multi-robot systems.

  • H. Jaleel and J. S. Shamma, "Distributed Submodular Minimization and Motion Coordination over Discrete State Space," in IEEE Tran. on Control of Network Systems, 2018.

  • H. Jaleel and J. S. Shamma, "Design Of Real-Time Implementable Distributed Suboptimal Control: An LQR Perspective," in IEEE Transactions on Control of Network Systems, vol. 5, no. 4, pp. 1717-1728, Dec. 2018 .

  • H. Jaleel, M. Abdelkader, and J. S. Shamma, "Real-Time Distributed Motion Planning with Submodular Minimization," in Proc. of IEEE Conference on Control Technology and Applications (CCTA), Copenhagen, 2018, pp. 885-890 .

  • M. Abdelkader, Y. Lu, H. Jaleel, and J. S. Shamma, "Distributed Real Time Control of Multiple UAVs in Adversarial Environment: Algorithm and Flight Testing Results," 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, 2018, pp. 6659-6664 .

Modeling and Analysis of Human Decisions in Societal Settings


An important thrust of the research at the iMass lab is to understand how individuals make decisions in societal settings and how individual decisions impact the behavior of a society in the long run. In particular, we focus on the following research problems

  • Identifying network characteristics that enable an individual or a group of individuals to influence the behavior of large population.

  • Comparing the transients and steady-state behavior of existing models of human decision making.

  • Developing novel behavior based models for human decision making in social dilemma situations.

  • Novel computationally efficient approaches for analyzing evolution dynamics.

This research is theoretical and our contributions are in the foundational area of learning in games and evolutionary dynamics.

  • B. Touri, H. Jaleel, and J. S. Shamma, "Stochastic Evolutionary Dynamics: A Graphical Reformulation of Evolutionarily Stable Strategy (ESS) Analysis," in IEEE Control Systems Letters, 2019 .

  • H. Jaleel and J. S. Shamma, "Path to stochastic stability: Comparative Analysis of Stochastic Learning Dynamics in Games," accepted for publication in IEEE Tran. on Automatic Control, 2019.

  • H. Jaleel and J. S. Shamma, "A Hierarchical Approach for the Stochastic Stability Analysis of Evolutionary Dynamics," accepted in IEEE CDC, 2020.

  • H. Jaleel, W. Abbas, and J. S. Shamma, "Robustness Of Stochastic Learning Dynamics To Player Heterogeneity In Games," in Proc. of IEEE 58th Conference on Decision and Control (CDC), Nice, France, 2019, pp. 5002-5007.

Mechanism Design for Sociotechnical Systems

Sociotechnical systems involve both humans and machines making decisions in a feedback configuration such that the decisions of both humans and machines impact the behavior of each other. Understanding this complex interplay between humans and machines provides a strong motivation for the research at the iMaSS Lab. In particular, we are working on problems related to smart agriculture and irrigation systems in Pakistan.

  • Developing efficient demand driven mechanisms for surface water distribution in the context of Pakistan.

  • Social network analysis of agriculture sector in Pakistan for introducing novel Sustainable Intensification practices.

This research is a result of active collaboration with Center for Water Informatics & Technology (WIT) at LUMS.

  • W. Hassan, H. Jaleel, T. Manzoor, and A. Muhammad, "A VCG Mechanism for Demand Management of Irrigation Systems," in Proc. of IFAC World Congress, Berlin, Germany, 2020.