Today marks the end of the first month of my current year-long sabbatical. I thought that this was as good a time as any to reflect on what I have accomplished so far, and to consider where my research is heading.
While the sabbatical is only officially one month old, the stage for the project was set in the fall term of 2016. In order to be fortunate enough to be awarded a sabbatical, one must apply for it, and part of this application involves proposing the kind of work that will be accomplished during the sabbatical. I have a long history of writing a book during each year-long sabbatical that I have been awarded; the plan for the current sabbatical was no different. I proposed using the time to draft a manuscript that extended some recent work in my lab on simple artificial neural networks and probability theory, and was lucky enough to be given the green light for this kind of project from the Faculty of Arts.
With a sabbatical plan required in the fall, it is not surprising that I was in a position to start groundwork for the current sabbatical at the end of the fall term. Much of that work has involved doing a lot of reading – since marking the final exam for my fall cognitive science course, I have read 23 books on systems theory, cybernetics, information theory, and probability. Those interested can see what I have been reading by looking through my Instagram account (https://www.instagram.com/drmrwdawson/) for pictures of covers. I use #reading to tag these posts. I have also conducted a pretty extensive simulation study (which has involved training and analyzing the performance of 500 different perceptrons) that explores how networks match the probability of outcomes in a three-cue probability learning task. In the fall, I plan to collect data from human subjects that are trained on the same task that I have used to train the networks; I am pretty excited about the main result that I expect to observe when networks and humans are compared. This has meant that I have also written programs to collect this data from humans. Importantly, I have also successfully navigated the process for getting ethics approval for this work; I haven’t collected human data for years. Most importantly, I have already crafted three complete chapters of a new book manuscript (when published, it will be my eighth book) that relate networks to probability theory and information theory, that explore the relationship between simple networks and Bayes’ theorem in probability, and that report the results of my simulations.