Research

I am currently working on argumentation-based dialogues for mutliagent planning towards my PhD dissertation. My goal is a theory and a preliminary implementation in which a group of autonomous agents (e.g. robots) can coordinate and plan their actions against an uncertain environment. The argumentation approach is to resolve conflicts arising from agents’ different views of the environment dynamics and their different goals about what to achieve. The approach is composed of two phases: argument construction and conflict pattern analysis. The argument construction is essentially an information clustering procedure in which information are gathered into arguments according to certain reasoning pattern (either a strict logic, a defeasible logic, statistical inferences, or their combinations). The conflict pattern analysis is a procedure to assign status (accepted, rejected, unknown, or other intermediate class of status) to the information clusters according to the conflict relation among these clusters with respect to the reasoning pattern being used. Then the agents exchange their information about the clusters and the conflict pattern according to the mechanism defined by a dialogue protocol. In this way, the agents will be expected to make decent decisions about their actions obeying the constraints imposed by their goals and the environment dynamics.

The research topics which I have been involved in:

• Using Argumentation-based Dialogues for Mutliagent Planning (dissertation topic, 2003 - present), under the supervision of Dr. Simon Parsons
• Agent-based Modeling Simulation of Education and Human Capital (2004 - present), under the supervision of Dr. Elizabeth Sklar and Dr. Simon Parsons
• Matrix Eigen problems and Polynomial Root-finding (2003 - 2005), under the supervision of Dr. Victor Pan

Not limited to the above topics, I am interested in:

• Multiagent Planning and Coordinations
• Dialogues and Argumentation Systems
• Multi-Robotics
• Machine Learning
• Matrix Eigen Problems: A matrix, its eigen values, and the corresponding eigen vectors together compose a very interesting mathematical structure. The direction of an eigen vector is invariant under the linear transformation represented by the matrix; this property shares some similarity with the goal of extracting certainties out of changes (uncertainties).
• and a lot more...