Serial dictatorship mechanisms with reservation prices: heterogeneous objects

We adapt a set of mechanisms introduced by Klaus and Nichifor (Econ Theory 70:665–684, 2020), serial dictatorship mechanisms with (individual) reservation prices, to the allocation of heterogeneous indivisible objects, e.g., specialist clinic appointments. We show how the characterization of serial dictatorship mechanisms with reservation prices for homogeneous indivisible objects (Klaus and Nichifor 2020, Theorem 1) can be adapted to the allocation of heterogeneous indivisible objects by adding neutrality: mechanism $$\varphi $$ φ satisfies minimal tradability, individual rationality, strategy-proofness, consistency, independence of unallocated objects, neutrality, and non wasteful tie-breaking if and only if there exists a reservation price vector r and a priority ordering $$\succ $$ ≻ such that $$\varphi $$ φ is a serial dictatorship mechanism with reservation prices based on r and $$\succ $$ ≻ .

Causal Non-Symmetry

Causation is a non-symmetric rather than asymmetric relation. Different bases of causal non-symmetry include an asymmetry of overdetermination, the independence condition, and agency. Causal non-symmetry can be rooted in one or more of these three while also recognizing a fourth non-symmetry appealing to a primitive non-symmetric chance-raising. Each counts as an appropriate basis for causal non-symmetry because it is a (partial) realization of non-symmetric chance-raising. Key moves involve a refinement of how to understand the way in which the asymmetry of overdetermination works, and how it interacts with the revised similarity weighting, the contribution of the independence condition to a proper understanding of the transition period, the role that appeals to primitive non-symmetric chance-raising should play in the treatment of problem cases, the circumstances in which an appeal to an interlevel non-symmetry of agency may be appropriate, and the priority ordering of these various realizations of causal non-symmetry.

Searching with Consistent Prioritization for Multi-Agent Path Finding

We study prioritized planning for Multi-Agent Path Finding (MAPF). Existing prioritized MAPF algorithms depend on rule-of-thumb heuristics and random assignment to determine a fixed total priority ordering of all agents a priori. We instead explore the space of all possible partial priority orderings as part of a novel systematic and conflict-driven combinatorial search framework. In a variety of empirical comparisons, we demonstrate state-of-the-art solution qualities and success rates, often with similar runtimes to existing algorithms. We also develop new theoretical results that explore the limitations of prioritized planning, in terms of completeness and optimality, for the first time.

Indoor Routing on Logical Network Using Space Semantics

An indoor logical network qualitatively represents abstract relationships between indoor spaces, and it can be used for path computation. In this paper, we concentrate on the logical network that does not have notions for metrics. Instead, it relies on the semantics and properties of indoor spaces. A navigation path can be computed by deriving parameters from these semantics and minimizing them in routing algorithms. Although previous studies have adopted semantic approaches to build logical networks, routing methods are seldom elaborated. The main issue with such networks is to derive criteria for path computation using the semantics of spaces. Here, we present a routing mechanism that is based on a dedicated space classification and a set of routing criteria. The space classification reflects characteristics of spaces that are important for navigation, such as horizontal and vertical directions, doors and windows, etc. Six routing criteria are introduced, and they involve: (1) the spaces with the preferred semantics; and/or (2) their centrality in the logical network. Each criterion is encoded as the weights to the nodes or edges of the logical network by considering the semantics of spaces. Logical paths are derived by a traditional shortest-path algorithm that minimizes these weights. Depending on the building’s interior configuration, one criterion may result in several logical paths. Therefore, we introduce a priority ordering of criteria to support path selection and decrease the possible number of logical paths. We provide a proof-of-concept implementation for several buildings to demonstrate the usability of such a routing. The main benefit of this routing method is that it does not need geometric information to compute a path. The logical network can be created using verbal descriptions only, and this routing method can be applied to indoor spaces derived from any building subdivision.

The structure of priority in the school choice problem

In a school choice problem, each school has a priority ordering over the set of students. These orderings depend on criteria such as whether a student lives within walking distance or has a sibling at the school. A priority ordering provides a ranking of students but nothing more. I argue that this information is sufficient when priority is based on merit but not when priority is based on criteria such as walking distance. I propose an extended formulation of the problem wherein a ‘priority matrix’, indicating which criteria are satisfied by each student-school pair, replaces the usual priority orderings.

Grounding and Reflexivity

Grounding is commonly assumed to induce a strict partial ordering: it is said to be asymmetric, transitive and irreflexive. Why it is that we ought to believe that grounding is irreflexive, in particular, appears to turn in large part on the impossibility of any instance of it being reflexive. But why is this? Indeed, how would things need to be such that anything could ground itself? And why is this so bad? This paper explores metaphysical and explanatory reasons for supposing that nothing can ground itself. The discussion centers on the thoughts that there are problems with bootstrapping, the priority ordering and necessary beings, and finds them wanting. A conclusion is reached that the best reasons we have for supposing that grounding is irreflexive are going to be epistemic rather than metaphysical.

Valencian Hypocoristics: When Morphology Meets Phonology

<p>Valencian hypocoristics constitute a domain in which morphology seems to be at rescue when phonological problems arise. The prosodic requirements of the truncated form (a disyllabic left-headed foot) determine the insertion of an inflectional exponent, i.e., 'morphological epenthesis'. The grammar avoids the insertion of regular epenthetic material and favors the choice of an exponent already listed in the lexicon. Assuming inflectional allomorphs to be underdetermined in the input, a constraint Priority ('respect lexical priority -ordering- of allomorphs', Mascaró 2007) is responsible for the assignment of exponents. In cases of phonological conflict, the interaction with markedness constraints forces the insertion of a marked allomorph in the hierarchy. In short, the proposal implies that phonology can control allomorph selection. </p>

Modelling a Nurse Shift Schedule with Multiple Preference Ranks for Shifts and Days-Off

When it comes to nurse shift schedules, it is found that the nursing staff have diverse preferences about shift rotations and days-off. The previous studies only focused on the most preferred work shift and the number of satisfactory days-off of the schedule at the current schedule period but had few discussions on the previous schedule periods and other preference levels for shifts and days-off, which may affect fairness of shift schedules. As a result, this paper proposes a nurse scheduling model based upon integer programming that takes into account constraints of the schedule, different preference ranks towards each shift, and the historical data of previous schedule periods to maximize the satisfaction of all the nursing staff's preferences about the shift schedule. The main contribution of the proposed model is that we consider that the nursing staff’s satisfaction level is affected by multiple preference ranks and their priority ordering to be scheduled, so that the quality of the generated shift schedule is more reasonable. Numerical results show that the planned shifts and days-off are fair and successfully meet the preferences of all the nursing staff.