Alan has been invited speaker at several conferences over the summer.
We will survey and summarise the typical methodologies used in computing research, including both theoretical and experimental methodologies. Our emphasis will be on best practice, ensuring the validity and highest quality of the results of your research. We will emphasise the importance of formulating precise and evaluable hypotheses or claims, making it clear to your readers what claims you are and are not making, then providing an evaluation that supports (or perhaps refutes) your claims. We will warn you about some of the most common pitfalls in computing research, so you avoid or recover from them.
Reformation: A Generic Algorithm for Repairing Faulty Logical Theories
Can Computers Change their Minds?
Autonomous agents require models of their environment in order to interpret sensory data and to make plans to achieve their goals, including anticipating the results of the actions of themselves and other agents. These models must change when the environment changes, including their models of other agents, or when their goals change, since successful problem solving depends on choosing the right representation of the problem. We are especially interested in conceptual change, i.e., a change of the language in which the model is expressed. Failures of reasoning can suggest repairs to faulty models. Such failures can, for instance, take the form of inferring something false, failing to infer something true or inference just taking too long. I will illustrate the automated repair of faulty models drawing both on work multi-agent planning and on the evolution of theories of physics.