Research Interests, Laura M. Grabowski

I am interested in both natural and computational intelligence. Evolution has discovered simple intelligent behaviors, and that process can provide insights that may be used to build computational solutions that exhibit the flexibility, adaptability, and robustness of natural systems.

The platform I use for my research is the Avida digital evolution platform (Ofria and Wilke, 2004). The Avida research platform subjects a population of self-replicating computer programs, or "digital organisms," to external pressures such as mutations and limited resources, and allows the programs to evolve through selection. Avida is an instance of real evolution, not simply a simulation; Avida organisms evolve to survive in complex computational environments, and evolve new survival strategies in unexpected and creative ways. Avida is a next-generation evolutionary computation system that allows for in-depth analysis of both the underlying evolutionary dynamics and the evolved algorithm, giving Avida a distinct advantage over many other evolutionary computation tools and approaches.

My research examines the evolutionary origin of memory and learning, capabilities that are crucial to intelligent behavior. I am addressing core issues relating to the evolution of memory and learning, such as how evolution produces complex memory structures and learning behaviors, and why building blocks that enable memory and learning are selected for. I am investigating these questions through Avida experiments that focus on how memory and learning become possible in evolution, and examining what strategies evolve and how those strategies build on one another.

My future research will continue to address basic questions that relate to intelligence. A common thread through my research is the idea of transitions: How do strategies change as a function of changes in the environment? The notion of transitions maps directly to the ideas of flexibility, adaptability, and robustness, and is relevant to many issues in Computer Science. I am interested in transitions related to capabilities that contribute to navigation, such as odometry and compasses (both internal and external). My goal is to discover computational approaches that provide the same degree of flexibility in these mechanisms that we observe in the navigation behavior of even simple animals, such as ants and bees, so that we can apply those strategies to future robot navigation systems.

Charles Ofria and Claus O. Wilke. Avida: a software platform for research in computational evolutionary biology. In Artificial Life 10, pages 191 - 229, 2004.