About Me

I am a doctoral student in Computer Science at UMass, where I work with Andrew Barto and Rod Grupen. I study a subfield of Artificial Intelligence called Developmental Robotics; for more about my research, see below. I graduated from Swarthmore College in 2003, and from the Illinois Mathematics and Science Academy in 1999--both were amazing, wonderful, formative places.

Research

Developmental robotics. Artificial intelligence, robotics, computational reinforcement learning, machine learning, development, artificial life, evolutionary computation, self-organization, complex adaptive systems, agent-based modeling.

Through my research I seek to understand the computational principles of systems that display continual, open-ended, endogenous adaptation, by synthesizing similarly autonomous and adaptive artificial systems.

My driving interest is in discovering representations and algorithms for constructive, grounded, long-term, domain-general cognitive and motor development in robots. Toward this end, I am studying principled, endogenous mechanisms for structuring and organizing developmental progression. I am focusing on two broad classes of such mechanisms: maturation and motivation. Maturation controls the complexity inherent in embodied learning by scheduling the resources available, and biases the learner to stimuli and tasks appropriate to the current stage of development. The motivational system also biases the attention of the learner on developmentally appropriate tasks, and drives the continual bootstrapping of increasingly sophisticated learning. I am eager to prove the utility of a developmental approach to endowing real robots with useful abilities.

I have a sustained, albeit neglected, secondary interest in complex systems, self-organization, and evolutionary computation; this interest is most at home in the multidisciplinary fields of Artificial Life and Complexity Science.

Publications

  • Andrew Stout, George Konidaris, and Andrew Barto - Intrinsically Motivated Reinforcement Learning: A Promising Framework For Developmental Robot Learning. Proceedings of the AAAI Spring Symposium on Developmental Robotics, 2005. [pdf]
  • Andrew Stout and Lee Spector - Validation of Evolutionary Activity Metrics for Long-Term Evolutionary Dynamics. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2005. [pdf]
  • Julie Corder, Oliver Hsu, Andrew Stout, and Bruce Maxwell - A Modular Software Architecture for Heterogeneous Robot Tasks. Proceedings of the AAAI Workshop on Mobile Robotics, 2002.