microPhantom: Playing microRTS under uncertainty and chaos

This competition paper presents microPhantom, a bot playing microRTS and participating in the 2020 microRTS AI competition. microPhantom is based on our previous bot POAdaptive which won the partially observable track of the 2018 and 2019 microRTS AI competitions. In this paper, we focus on decision-making under uncertainty, by tackling the Unit Production Problem with a method based on a combination of Constraint Programming and decision theory. We show that using our method to decide which units to train improves significantly the win rate against the second-best microRTS bot from the partially observable track. We also show that our method is resilient in chaotic environments, with a very small loss of efficiency only. To allow replicability and to facilitate further research, the source code of microPhantom is available, as well as the Constraint Programming toolkit it uses

The Faculty Notebook, September 2019

The Faculty Notebook is published periodically by the Office of the Provost at Gettysburg College to bring to the attention of the campus community accomplishments and activities of academic interest. Faculty are encouraged to submit materials for consideration for publication to the Associate Provost for Faculty Development. Copies of this publication are available at the Office of the Provost

Randomization tests for peer effects in group formation experiments

Measuring the effect of peers on individual outcomes is a challenging problem, in part because individuals often select peers who are similar in both observable and unobservable ways. Group formation experiments avoid this problem by randomly assigning individuals to groups and observing their responses; for example, do first-year students have better grades when they are randomly assigned roommates who have stronger academic backgrounds? Standard approaches for analyzing these experiments, however, are heavily model-dependent and generally fail to exploit the randomized design. In this paper, we extend methods from randomization-based testing under interference to group formation experiments. The proposed tests are justified by the randomization itself, require relatively few assumptions, and are exact in finite samples. First, we develop procedures that yield valid tests for arbitrary group formation designs. Second, we derive sufficient conditions on the design such that the randomization test can be implemented via simple random permutations. We apply this approach to two recent group formation experiments

What Will Recruitment Look Like in Five Years and What Will Be Different From Today?

[Excerpt] Across most companies today, recruitment continues to follow the traditional model – hiring managers present lists of desired qualifications and responsibilities through job descriptions, applicants submit chronological summaries of their work experience, and recruiters review applications through the applicant tracking system to identify relevant skills and experience. In the next five to ten years, this model of recruitment will transform significantly. There are many reasons for this. First, careers today are more lattice-like, and less linear. Individuals’ career paths are characterized by shorter tenures, stretch assignments, entrepreneurial endeavors, time off work to spend with family, and gig work. The recruitment process should change to account for these “jagged resumes”. Second, as automation, robotics, and Artificial Intelligence (AI) take over manual, repetitive tasks, the work left to be performed by humans will be more creative and strategic, less predictable, and more consequential to the business overall. The stakes of making the right hire will increase, and recruiting will become a defining differentiator. Already, demand for recruiting professionals is up 63% since 2016. Lastly, as companies prepare for the future of work, recruitment practices will need to change to match new trends and challenges. For example, 50% of millennials are already freelancing, and this number is expected to rise significantly. 43% of college Gen Z’s are eyeing an entrepreneurial future over traditional workplaces. Given these broad trends, the future of recruitment will be marked by changes in three domains – recruitment technology, skills that companies recruit for, and the competencies of recruitment teams in the future

A perturbative study of holographic mABJM theory

Recently the calculation of holographic free energy for mass-deformed ABJM model (mABJM) with ${\cal N}=2$ supersymmetry and $SU(3)\times U(1)$ global symmetry was tackled by Bobev et al. in arXiv:1812.01026. We solve the associated BPS equations, requiring IR regularity, using a perturbative method proposed by one of us recently in axXiv:1902.00418. In particular, we provide an analytic proof of a crucial conjecture made in arXiv:1812.01026 based on numerical solutions: that the R-charge values of three chiral multiplets in mABJM should be independent of the IR values of a hypermultiplet scalar, which is holographically dual to the superpotential mass term.Comment: 15 pages, 1 figur