A Learning Based Approach to Control Synthesis of Markov Decision Processes for Linear Temporal Logic Specifications

We propose to synthesize a control policy for a Markov decision process (MDP) such that the resulting traces of the MDP satisfy a linear temporal logic (LTL) property. We construct a product MDP that incorporates a deterministic Rabin automaton generated from the desired LTL property. The reward function of the product MDP is defined from the acceptance condition of the Rabin automaton. This construction allows us to apply techniques from learning theory to the problem of synthesis for LTL specifications even when the transition probabilities are not known a priori. We prove that our method is guaranteed to find a controller that satisfies the LTL property with probability one if such a policy exists, and we suggest empirically with a case study in traffic control that our method produces reasonable control strategies even when the LTL property cannot be satisfied with probability one

Creating the Optimum Classroom Environment in Counselor Education Using Group Leadership Skills

Most counselor educators are not trained in teaching, but many possess group facilitation skills. Counselor educators can capitalize on these skills and intentionally strive to provide an optimal learning environment in the classroom utilizing the basic concepts and techniques applied in group leadership. The following article suggests applying a group work perspective to inform a pedagogical approach when teaching graduate level counseling courses

Precision gamma-ray constraints for sub-GeV dark matter models

The indirect detection of dark matter particles with mass below the GeV scale has recently received significant attention. Future space-borne gamma-ray telescopes, including All-Sky-ASTROGAM, AMEGO, and GECCO, will probe the MeV gamma-ray sky with unprecedented precision, offering an exciting test of particle dark matter in the MeV-GeV mass range. While it is typically assumed that dark matter annihilates into only one Standard Model final state, this is not the case for realistic dark matter models. In this work we analyze existing indirect detection constraints and the discovery reach of future detectors for the well-motivated Higgs and vector-portal models using our publicly-available code Hazma. In particular, we show how to leverage chiral perturbation theory to compute the dark matter self-annihilation cross sections into final states containing mesons, the strongly-interacting Standard Model dynamical degrees of freedom below the GeV scale. We find that future telescopes could probe dark matter self-annihilation cross sections orders of magnitude smaller than those presently constrained by cosmic microwave background, gamma-ray and terrestrial observations.Comment: 20 pages, 4 figure

Direct Detection of Hawking Radiation from Asteroid-Mass Primordial Black Holes

Light, asteroid-mass primordial black holes, with lifetimes in the range between hundreds to several millions times the age of the Universe, are well-motivated candidates for the cosmological dark matter. Using archival COMPTEL data, we improve over current constraints on the allowed parameter space of primordial black holes as dark matter by studying their evaporation to soft gamma rays in nearby astrophysical structures. We point out that a new generation of proposed MeV gamma-ray telescopes will offer the unique opportunity to directly detect Hawking evaporation from observations of nearby dark matter dense regions and to constrain, or discover, the primordial black hole dark matter