bluuebunny/crossref_metadata_2025 huggingface dataset:
Designing Network Practices (Using the Example of Religious Communities)
Authors:   Ural State Pedagogical University, Porozov Roman Yu.
Published: September 2022

The study of social networks and Internet practices of Russian religious communities has been of a long­term nature — since the appearance and presentation of the first online communities. Religious online communities have received a new tool for broadcasting their own ethos and theological meanings. The article discusses the strategy of enlightenment in the practice of organizing religious communities on the Internet (on the example of the social media VKontakte). The purpose of this article is an attempt to determine the specifics of the main practices and strategies of enlightenment, publicly represented by religious network communities in the external environment. By educational practice, the author understands such a system of actions in which the results — regardless of the form of their presentation — are motivated and conditioned by the installation to represent as much as possible, consciously endure and explain in the public space one’s specific religious ethos, a religious picture of the world; it is an action and a result that is directed to an external viewer. The empirical base of the study was more than 430 religious and theological communities on VKontakte; the study period is April — November 2021. The author identifies four main types of enlightenment strategy, publicly represented by religious network communities in the external environment: classical, everyday (routine\regular), individualized, sacralizing. We note that the tendencies, regularities, and specifics of the cultural activity of a religious person in the virtual space are similar to the behavior in the real space. The results of the study can be used as a basis for analyzing the motivational strategies of a person’s religious behavior in the network, as well as in the development of educational materials in the course “Fundamentals of Religious Cultures and Secular Ethics” and others.
Aesthetic Positions of Symbolism in the Works of Iraqi Artists 1970–1990
Authors:   Ural Federal University, Al-Chalabi Omar Fawwaz
Published: September 2022

The article is devoted to the study of the aesthetics of symbolism in the works of contemporary Iraqi artists of the 1970s–1990s. The purpose of the study is to analyze the content of symbols in the works of Iraqi symbolist artists in the context of historical and cultural events of the country. The author uses descriptive, analytical, comparative historical methods of scientific research. A brief history of Iraqi symbolism is given. The analysis of the works of Iraqi symbolist artists such as M. Ahmad, V. Sheit, R. Dabdub, D. Azzawi, Sh. H. Al Said is carried out, which allows to clarify the symbolism of Iraqi painting of the 1970s–1990s.
The Influence of the Principles of Network Interaction on Educational Systems (on the Example of the Art Education System of the Sverdlovsk Region)
Authors:   The Russian Presidential Academy of National Economy and Public Administration, Kleshcheva Natalia V.
Published: September 2022

The key idea of the study is to consider the network interaction between the subjects of the educational system. The purpose of the study is to analyze the features of the formation of an educational network community. The object of the study is network communities in the field of art education. The importance of effective interaction and continuity of the three-stage system of art education as key factors in the formation of an educational network community is highlighted and the problematic field of its formation is determined.
Terapia ocupacional e redes intersetoriais: conceitos e experiências em debate
Authors: Avelar Mariana Rossi , Malfitano Ana Paula Serrata
Published: September 2022

Resumo A formação de redes como estratégia de ação técnica tem se caracterizado como uma temática amplamente defendida no bojo das políticas sociais, as quais são historicamente organizadas em setores e precisam ter suas atuações reorganizadas em vista das cada vez mais complexas demandas sociais. O trabalho em rede é compreendido como um recurso de enfrentamento à questão social e suas consequências, e como ferramenta para efetivação de propostas de intervenção junto à população assistida. A terapia ocupacional pode utilizar da criação e/ou fortalecimento das redes sociais como processos que buscam garantir maior autonomia e inserção social a pessoas ou grupos que vivenciam processos de ruptura em suas vidas. Objetivou-se investigar a estratégia de articulação intersetorial entre os serviços que compõem as políticas sociais em Campinas - SP como possível ferramenta de suporte, enfocando a atuação de terapeutas ocupacionais. Como método, 13 coordenadores distritais das áreas de assistência social, educação e saúde foram entrevistadas e 17 das 36 terapeutas ocupacionais (47%) que atuam na rede municipal responderam a um questionário. Além disso, observou-se duas redes institucionais por quatro meses. Por fim, nove terapeutas ocupacionais participaram de um encontro presencial para discutir sua experiência e papel nas redes. Aqui analisam-se os dados dos questionários e grupo com as profissionais. Conclui-se que, considerando a centralidade da (re)inserção social como objetivo da terapia ocupacional, somada a características como disponibilidade e flexibilidade, o fomento de redes intersetoriais é integrado ao seu trabalho; contudo, essa não pode ser considerada uma ação profissional específica ou exclusiva.
A POLÍTICA EXTERNA DO BRASIL NOS TEMPOS DO GOVERNO BOLSONARO
Authors: Hirst Monica , Maciel Tadeu
Published: September 2022

Este artigo produz um mapeamento sobre os principais pilares da política externa do governo Bolsonaro no Brasil e representa uma primeira busca de racionalidade para compreender a política externa do governo Bolsonaro como parte do projeto de poder vigente no Brasil. Com tal propósito, são identificados e brevemente caracterizados os três pilares sobre os quais essa política se sustenta (“núcleo político ideológico”, “política econômica liberal-conservadora” e que o complexo de “segurança e defesa”). Esta tripla sustentação é avaliada a partir dos âmbitos doméstico, internacional e regional. O prisma analítico que orienta essa caracterização supõe a política externa como uma política pública, que envolve um arco abrangente de atores e interesses. Tal arco implica uma coabitação de cooperação e competição entre os segmentos sociais, políticos e econômicos que nutrem a agenda externa do governo Bolsonaro. Entre valores conservadores e má gestão na pandemia, fica evidente o inexistente espaço prioritário conferido ao relacionamento com o entorno estratégico.
Dynamic Controllability of Temporally-flexible Reactive Programs
Authors: Effinger Robert , Williams Brian , Kelly Gerard , Sheehy Michael
Published: September 2022

In this paper we extend dynamic controllability of temporally-flexible plans to temporally-flexible reactive programs.  We consider three reactive programming language constructs whose behavior depends on runtime observations; conditional execution, iteration, and exception handling. Temporally-flexible reactive programs are distinguished from temporally-flexible plans in that program execution is conditioned on the runtime state of the world.  In addition, exceptions are thrown and caught at runtime in response to violated timing constraints, and handled exceptions are considered successful program executions.  Dynamic controllability corresponds to a guarantee that a program will execute to completion, despite runtime constraint violations and uncertainty in runtime state.  An algorithm is developed which frames the dynamic controllability problem as an AND/OR search tree over possible program executions.  A key advantage of this approach is the ability to enumerate only a subset of possible program executions that guarantees dynamic controllability, framed as an AND/OR solution subtree.
Multi-Goal Planning for an Autonomous Blasthole Drill
Authors: Elinas Pantelis
Published: September 2022

This paper presents multi-goal planning for an autonomous blasthole drill used in open pit mining operations. Given a blasthole pattern to be drilled and constraints on the vehicle's motion and orientation when drilling, we wish to compute the best order in which to drill the given pattern. Blasthole pattern drilling is an asymmetric Traveling Salesman Problem with precedence constraints specifying that some holes must be drilled before others. We wish to find the minimum cost tour according to criteria that minimize the distance travelled satisfying the precedence and vehicle motion constraints. We present an iterative method for solving the blasthole sequencing problem using the combination of a Genetic Algorithm and motion planning simulations that we use to determine the true cost of travel between any two holes.
Exploiting N-Gram Analysis to Predict Operator Sequences
Authors: Muise Christian , McIlraith Sheila , Baier Jorge , Reimer Michael
Published: September 2022

N-gram analysis provides a means of probabilistically predicting the next item in a sequence. Due originally to Shannon, it has proven an effective technique for word prediction in natural language processing and for gene sequence analysis. In this paper, we investigate the utility of n-gram analysis in predicting operator sequences in plans. Given a set of sample plans, we perform n-gram analysis to predict the likelihood of subsequent operators, relative to a partial plan. We identify several ways in which this information might be integrated into a planner. In this paper, we investigate one of these directions in further detail. Preliminary results demonstrate the promise of n-gram analysis as a tool for improving planning performance.
Planning Problems for Social Robots
Authors: Tipaldi Gian Diego , Arras Kai
Published: September 2022

As robots enter environments that they share with people, human-aware planning and interaction become key tasks to be addressed. For doing so, robots need to reason about the places and times when and where humans are engaged into which activity and plan their actions accordingly. In this paper, we first address this issue by learning a nonhomogenous spatial Poisson process whose rate function encodes the occurrence probability of human activities in space and time. We then present two planning problems for human robot interaction in social environments. The first one is the maximum encounter probability planning problem, where a robot aims to find the path along which the probability of encountering a person is maximized. We are interested in two versions of this problem, with deadlines or with a certainty quota. The second one is the minimum interference coverage problem, where a robot performs a coverage task in a socially compatible way by reducing the hindrance or annoyance caused to people. An example is a noisy vacuum robot that has to cover the whole apartment having learned that at lunch time the kitchen is a bad place to clean. Formally, the problems are time dependent variants of known planning problems: MDPs and price collecting TSP for the first problem and the asymmetric TSP for the second. The challenge is that the cost functions of the arcs and nodes vary with time, and that execution time is more important that optimality, given the real-time constraints in robotic systems. We present experimental results using variants of known planners and formulate the problems as benchmarks to the community.
Program Committee
Authors: Bonet Blai
Published: September 2022

Program committee members of the 2012 ICAPs conference.
Predicting Optimal Solution Cost with Bidirectional Stratified Sampling
Authors: Lelis Levi , Stern Roni , Felner Ariel , Zilles Sandra , Holte Robert
Published: September 2022

Optimal planning and heuristic search systems solve state-space searchproblems by finding a least-cost path from start to goal. As a byproduct of having an optimal path they also determine the optimal solution cost. In this paper we focus on the problem of determining the optimal solution cost for a state-space search problem directly, i.e. without actually finding a solution path of that cost. We present an efficient algorithm, BiSS, based on ideas of bidirectional search and stratified sampling that produces accurate estimates of the optimal solution cost. Our method is guaranteed to return the optimal solution cost in the limit as the sample size goes to infinity.We show empirically that our method makes accurate predictions in several domains. In addition, we show that our method scales to state spaces much larger than can be solved optimally. In particular, we estimate the average solution cost for the 6x6, 7x7, and 8x8 Sliding-Tile Puzzle and provide indirect evidence that these estimates are accurate.
Searching for Good Solutions in Goal-Dense Search Spaces
Authors: Coles Amanda , Coles Andrew
Published: September 2022

In this paper we explore the challenges surrounding searching effectively in problems with preferences.  These problems are characterized by a relative abundance of goal states: at one extreme, if every goal is soft, every state is a goal state.  We present techniques for planning in such search spaces, managing the sometimes-conflicting aims of intensifying search around states on the open list that are heuristically close to new, better goal states; and ensuring search is sufficiently diverse to find new low-cost areas of the search space, avoiding local minima.  Our approach uses a novel cost-bound-sensitive heuristic, based on finding several heuristic distance-to-go estimates in each state, each satisfying a different subset of preferences.  We present results comparing our new techniques to the current state-of-the-art and demonstrating their effectiveness on a wide range of problems from recent International Planning Competitions.
Planning Solar Array Operations on the International Space Station
Authors: Frank Jeremy
Published: September 2022

Flight controllers manage the orientation and modes of eight large solar arrays that power the International Space Station (ISS). The task requires generating plans that balance complex constraints and preferences. These considerations include context-dependent constraints on viable solar array configurations, temporal limits on transitions between configurations, and preferences on which considerations have priority. The Solar Array Constraint Engine (SACE) treats this operations planning problem as a sequence of tractable constrained optimization problems. SACE uses constraint management and automated planning capabilities to reason about the constraints, to find optimal array configurations subject to these constraints and solution preferences, and to automatically generate solar array operations plans.
Timeline-Based Planning for Engaging Training Experiences
Authors: Cortellessa Gabriella , De Benedictis Riccardo , Pagani Marco
Published: September 2022

This paper reports on a novel use of timeline-based planning as the core element of a dynamic training environment specifically designed for crisis managers. It describes an effort to build a complete application that helps the trainer to create and deliver engaging and personalized training lessons for decision making skills in crisis management domains. The paper emphasis is given to (a) the timeline-based representation as the core component for creating training sessions and a trainee's model; (b) the combination of planning and execution functionalities required to maintain and dynamically adapt a "lesson plan" on the basis of individual interactions, behaviors and performance; (c) the "mixed-initiative" approach pursued, that allows the trainer to keep control of the activity loop. The application has been fielded and evaluated through a psychophysiological assessment within a real crisis training room involving 18 real strategic decision makers in a three-days of classes experience, overall demonstrating the ability of the system to fully support trainees engagement thanks to the flexibility injected by the planning technology.
Safe, Strong, and Tractable Relevance Analysis for Planning
Authors: Haslum Patrik , Helmert Malte , Jonsson Anders
Published: September 2022

In large and complex planning problems, there will almost inevitably be aspects that are not relevant to a specific problem instance. Thus, identifying and removing irrelevant parts from an instance is one of the most important techniques for scaling up automated planning. We examine the path-based relevance analysis method, which is safe (preserves plan existence and cost) and powerful but has exponential time complexity, and show how to make it run in polynomial time with only a minimal loss of pruning power.
Evaluating Diversity in Classical Planning
Authors: Roberts Mark , Howe Adele , Ray Indrajit
Published: September 2022

Applications that require alternative plans challenge the single solution, single quality metric assumptions upon which many classical planners are designed and evaluated. To evaluate the distinctness of alternative plans (i.e., plan sets), researchers have created diversity metrics that often measure the set difference between the actions of plans. Many approaches for generating plan sets embed the same diversity metric in a weighted evaluation function to guide the search mechanism, thus confounding the search process with its evaluation. We discover that two diversity metrics fail to distinguish similar plans from each other or to identify plans with extraneous actions, so we introduce two new diversity metrics, \emph{uniqueness} and \emph{overlap}, to capture these cases. We then examine the tradeoffs of producing diverse plans while we control for plan length and metric interaction and confirm that metric interaction can significantly impact search performance. We show that planners searching for plan sets must consider a third metric, \emph{parsimony}, that prefers shorter plans while maximizing diversity.We evaluate three existing approaches for generating diverse plans and two new algorithms that are designed to explicitly manage diversity and interaction between the diversity and quality metrics. Our findings synthesize and extend recent results in plan diversity.
Property Directed Reachability for Automated Planning
Authors: Suda Martin
Published: September 2022

Property Directed Reachability (PDR), also known as IC3, is a very promising recent method for deciding reachability in symbolically represented transition systems. While originally conceived as a model checking algorithm for hardware circuits, it has already been successfully applied in several other areas. This paper summarizes the first investigation of PDR from the perspective of automated planning.
Planning for Mining Operations with Time and Resource Constraints
Authors: Lipovetzky Nir , Burt Christina , Pearce Adrian , Stuckey Peter
Published: September 2022

We study a daily mine planning problem where, given a set of blocks we wishto mine, our task is to generate a mining sequence for the excavators suchthat blending resource constraints are met at various stages of thesequence. Such time-oriented resource constraintsare not traditionally handled well by automated planners. On the other hand,the remaining problem involves finding node-disjoint sequences withstate-dependent travel times on the arcs, which are highly challenging for a Mixed-Integer Program (MIP).In this paper, we address the problem of finding feasible sequences using a combined MIP and planning based decomposition approach. The MIP takes care of the resource constraints, and the planner solves the remaining sequence problem. We extend the notion of finding feasible sequences to finding good feasible sequences, by devising a heuristic objective function in the MIP, which improves the resulting search space for the planner.We empirically analyse the scalability of our approach on a benchmark data set, before demonstrating its effectiveness on a real world case study provided by our industry partner. These results demonstrate that by using a heuristic MIP, it is possible to obtain better makespan results with a suboptimal planner than by using an optimal planner with an uninformed MIP.
Planning meets Data Cleansing
Authors: Boselli Roberto , Cesarini Mirko , Mercorio Fabio , Mezzanzanica Mario
Published: September 2022

One of the motivations for research in data quality is to automatically identify cleansing activities, namely a sequence of actions able to cleanse a dirty dataset, which today are often developed manually by domain-experts. Here we explore the idea that AI Planning can contribute to identify data inconsistencies and automatically fix them. To this end, we formalise the concept of cost-optimal Universal Cleanser — a collection of cleansing actions for each data inconsistency — as a planning problem. We present then a motivating government application in which it has be used.
Analyzing the Impact of Partial States on Duplicate Detection and Collision of Frontiers
Authors: Alcázar Vidal , Fernández Susana , Borrajo Daniel
Published: September 2022

Partial states are states in which the truth value of one or more propositions is unknown. Such states are usually generated in regression and represent not a single state but rather a set of states. Because of this, a new partial state can be a subset of another existent partial state, phenomenon known as subsumption of states. Subsumed states can be pruned as if they were a duplicate. However, regular duplicate detection methods cannot detect such cases. Furthermore, subsumption of states also occurs when forward and backward search algorithms are integrated into a bidirectional planner. In these cases, the forward frontier contains only complete states and the backward frontier will often contain partial states. In this work, we analyze the impact that subsumption of states has on search and propose methods for duplicate detection and detection of collision of frontiers.
Under-Approximation Refinement for Classical Planning
Authors: Heusner Manuel , Wehrle Martin , Pommerening Florian , Helmert Malte
Published: September 2022

A general and important problem of search-based planning techniques is the state explosion problem, which is usually tackled with approaches to reduce the branching factor of the planning task. Such approaches often implicitly exploit the observation that the number of available operators is higher than the number of operators that are actually needed to find a plan. In this paper, we propose a simple, but general under-approximation refinement framework for satisficing planning that explicitly exploits this observation. Our approach iteratively searches for plans with operator subsets, which are refined if necessary by adding operators that appear to be needed. Our evaluation shows that even a straight-forward instantiation of this framework yields a competitive planner that often finds plans with small operator sets.
Policy Evaluation with Temporal Differences: A Survey and Comparison (Extended Abstract)
Authors: Dann Christoph , Neumann Gerhard , Peters Jan
Published: September 2022

Value functions are an essential tool for solving sequential decision making problems such as Markov decision processes (MDPs). Computing the value function for a given policy (policy evaluation) is not only important for determining the quality of the policy but also a key step in prominent policy-iteration-type algorithms. In common settings where a model of the Markov decision process is not available or too complex to handle directly, an approximation of the value function is usually estimated from samples of the process. Linearly parameterized estimates are often preferred due to their simplicity and strong stability guarantees. Since the late 1980s, research on policy evaluation in these scenarios has been dominated by temporal-difference (TD) methods because of their data-efficiency. However, several core issues have only been tackled recently, including stability guarantees for off-policy estimation where the samples are not generated by the policy to evaluate. Together with improving sample efficiency and probabilistic treatment of uncertainty in the value estimates, these efforts have lead to numerous new temporal-difference algorithms. These methods are scattered over the literature and usually only compared to most similar approaches. The article therefore aims at presenting the state of the art of policy evaluation with temporal differences and linearly parameterized value functions in discounted MDPs as well as a more comprehensive comparison of these approaches.We put the algorithms in a unified framework of function optimization, with focus on surrogate cost functions and optimization strategies, to identify similarities and differences between the methods. In addition, important extensions of the base methods such as off-policy estimation and eligibility traces for better bias-variance trade-off, as well as regularization in high dimensional feature spaces, are discussed.
Understanding and Improving Local Exploration for GBFS
Authors: Xie Fan , Müller Martin , Holte Robert
Published: September 2022

Greedy Best First Search (GBFS) is a powerful algorithm at the heart of many state-of-the-art satisficing planners. The Greedy Best First Search with Local Search (GBFS-LS) algorithm adds exploration using a local GBFS to a global GBFS. This substantially improves performancefor domains that contain large uninformative heuristic regions (UHR), such as plateaus or local minima. This paper analyzes, quantifies and improves the performance of GBFS-LS.Planning problems with a mix of small and large UHRs are shown to be hard for GBFS but easy for GBFS-LS. In three standard IPC planning instances analyzed in detail, adding exploration using local GBFS gives more than three orders of magnitude speedup. As a second contribution, the detailed analysis leads to an improvedGBFS-LS algorithm, which replaces larger-scale local GBFS explorations with a greater number of smaller explorations.
Temporal Flexibility Revisited: Maximizing Flexibility by Computing Bipartite Matchings
Authors: Mountakis Simon , Klos Tomas , Witteveen Cees
Published: September 2022

We discuss two flexibility metrics for Simple Temporal Networks (STNs): the so-called naive flexibility metric based on the difference between earliest and latest starting times of temporal variables, and a recently proposed concurrent flexibility metric. We establish an interesting connection between the computation of these flexibility metrics and properties of the minimal distance matrix DS of an STN S: the concurrent flexibility metric can be computed by finding a minimum weight matching of a weighted bipartite graph completely specified by DS, while the naive flexibility metric corresponds to computing a maximum weight matching in the same graph. From a practical point of view this correspondence offers an advantage: instead of using an O(n5) LP-based approach, reducing the problem to a matching problem we derive an O(n3) algorithm for computing the concurrent flexibility metric.
Planning Robust Manual Tasks in Hierarchical Belief Spaces
Authors: Lanighan Michael , Takahashi Takeshi , Grupen Roderic
Published: September 2022

This paper introduces a technique for planning in hierarchical belief spaces and demonstrates the idea in an autonomous assembly task. The objective is to effectively propagate belief across multiple levels of abstraction to make control decisions that expose useful state information, manage uncertainty and risk, and actively satisfy task specifications. This approach is demonstrated by performing multiple instances of a simple class of assembly tasks using the uBot-6 mobile manipulator with a two-level hierarchy that manages uncertainty over objects and assembly geometry. The result is a method for composing a sequence of manual interactions that causes changes to the environment and exposes new information in order to support belief that the task is satisfied. This approach has the added virtue that it provides a natural way to accomplish tasks while simultaneously suppressing errors and mitigating risk. We compare performance in an example assembly task against a baseline hybrid approach that combines uncertainty management with a symbolic planner and show statistically significant improvement in task outcomes. In additional demonstrations that challenge the system we highlight useful artifacts of the approach---risk management and autonomous recovery from unexpected events.
Incremental Search for Counterexample-Guided Cartesian Abstraction Refinement
Authors: Seipp Jendrik , Von Allmen Samuel , Helmert Malte
Published: September 2022

Counterexample-guided Cartesian abstraction refinement has been shown to yield informative heuristics for optimal classical planning. The algorithm iteratively finds an abstract solution and uses it to decide how to refine the abstraction. Since the abstraction grows in each step, finding solutions is the main bottleneck of the refinement loop. We cast the refinements as an incremental search problem and show that this drastically reduces the time for computing abstractions.
Predicting the Effectiveness of Bidirectional Heuristic Search
Authors: Sturtevant Nathan R. , Shperberg Shahaf , Felner Ariel , Chen Jingwei
Published: September 2022

The question of when bidirectional heuristic search outperforms unidirectional heuristic search has been revisited numerous times in the field of Artificial Intelligence. This paper re-addresses the question of when bidirectional search outperforms unidirectional search using an updated theoretical understanding of the problem. We show that a core set of critical states in the state space are the primary factor determining whether a bidirectional search can outperform a unidirectional search and provide simple measures to determine whether a state space and heuristic contains these critical states. We similarly discuss and show the impact that asymmetry in the underlying problem graph has on the performance of bidirectional algorithms. Experimental results show the impact of these factors on whether a problem should be solved using unidirectional or bidirectional search.
Online Hedge Reservation for Diverse Plans and Competitive Analysis
Authors: Wu Binghan , Bao Wei , Yuan Dong , Zhou Bing
Published: September 2022

In this paper, we investigate the plan reservation problem with diverse plans in mobile networks. The pricing scheme includes: 1) Pay-as-you-go (PAYG) payment; 2) All-in-one plan: an upfront fee is charged to cover data volume of a period of time; and 3) Directional plan: an upfront fee is charged to cover data volume of a specific app for a period of time. We investigate online plan reservation with competitive analysis, as the data volume is not known until an app is used. The problem is challenging as there are multiple directional plans and one all-in-one plan, creating a large decision space and complicated correlations among the decisions. We propose the Online Hedge Reservation (OHR) Algorithm to solve the problem and prove that it achieves e^beta/(e^beta-1) competitive ratio when each plan is valid till the end of each calendar month and 2e^beta/(e^beta-1) competitive ratio when each plan is valid for a full month, where beta is the ratio of prices of the directional plans and the all-in-one plan. This is an exciting neat extension of the competitive ratio e/(e-1) of the classic ski-rental problem. Finally, trace-driven simulation is conducted to further verify the advantages of the OHR Algorithm.
Hierarchical Freespace Planning for Navigation in Unfamiliar Worlds
Authors: Korpan Raj , Epstein Susan L.
Published: September 2022

Autonomous navigation in a large, complex space requires a spatial model, but the construction of a detailed map is costly. This paper demonstrates how two kinds of exploration support an alternative to metric mapping, one that facilitates robust hierarchical path planning. High-level exploration builds a global spatial model whose connectivity supports an effective, efficient, freespace planner, while low-level, target-driven exploration addresses areas where the global model lacks knowledge. Empirical results demonstrate successful and efficient travel in three challenging worlds.
On the Complexity of Heuristic Synthesis for Satisficing Classical Planning: Potential Heuristics and Beyond
Authors: Helmert Malte , Sievers Silvan , Rovner Alexander , B. Corrêa Augusto
Published: September 2022

Potential functions are a general class of heuristics for classical planning. For satisficing planning, previous work suggested the use of descending and dead-end avoiding (DDA) potential heuristics, which solve planning tasks by backtrack-free search. In this work we study the complexity of devising DDA potential heuristics for classical planning tasks. We show that verifying or synthesizing DDA potential heuristics is PSPACE-complete, but suitable modifications of the DDA properties reduce the complexity of these problems to the first and second level of the polynomial hierarchy. We also discuss the implications of our results for other forms of heuristic synthesis in classical planning.
CONCENTRATING SOLAR POWERED TRANSCRITICAL CO2 POWER GENERATION CYCLE FOR THE UNION TERRITORY OF LADAKH, INDIA
Authors: Hoque Syed Jiaul , Kumar Pramod , Dutta Pradip
Published: September 2022

High solar irradiation, cloud-free dry climate, abundant barren land, and low ambient temperature make the Union Territory of Ladakh, India, suitable for concentrating solar thermal power (CSP) plants. The present study comprehensively analyzes a 5 MW transcritical CO2 Rankine cycle power tower CSP plant. Low ambient temperature of the region allows transcritical operation, which provides high cycle efficiency. The study focuses on five aspects: solar field and thermal energy storage (TES), thermodynamic cycle simulation, turbomachines, and off-design performance analysis. Modeling and optimization of the solar field are undertaken to capture the diurnal and annual variations of direct normal irradiation levels using System Advisor Model open source software. Molten salt TES is integrated to overcome the dynamic variations of solar energy by providing stable operations and additional hours. The effect of storage sizes, starting from no storage to 12 hours, on the solar field size and specifications is also assessed. An in-house algorithm is developed for thermodynamic cycle optimization, exergy analysis, and off-design operations. The turbomachines of the cycle are designed using in-house meanline codes, and 3D CFD simulations are conducted for efficiency estimations. The effects of ambient temperature variations on the low side saturation pressure, cycle efficiency, and power output are evaluated. The proposed plant offers annual optical efficiency of 54.1%, thermal efficiency of 36.5%, and overall efficiency of 19.7%.
La fotografía en el diseño de los títulos de crédito de las películas de Pedro Almodóvar
Authors: Parejo Nekane
Published: September 2022

La preocupación del director Pedro Almodóvar por los elementos estéticos de sus películas es uno de los rasgos que definen su trayectoria y alcanza al diseño de los títulos de crédito como carta de presentación de sus producciones. Desde esta premisa, la investigación se ha centrado en la fotografía como un elemento que contribuye a su diseño gráfico. Para abordar esta cuestión, nos hemos propuesto tres objetivos específicos: determinar las fórmulas que emplea este cineasta para acoger imágenes fotográficas en el diseño gráfico de los títulos de crédito, comparar las aperturas y los créditos de cierre y establecer sus rasgos característicos en función de los contenidos visuales que emplean y su relación con los personajes y narración cinematográfica en Mujeres al borde de un ataque de nervios (1988), Tacones lejanos (1991) y La mala educación (2004). Metodológicamente nos hemos servido de la versión cualitativa del análisis de contenido, donde a partir de la filmografía completa de Pedro Almodóvar hemos seleccionado una muestra delimitada en función de los títulos de crédito  que cuentan con imágenes fotográficas. Para fijar las categorías se ha elaborado una clasificación propia que parte de Inceer y Vanoye para el estudio de los motivos visuales, de Laibag para la relación entre los títulos de crédito y la narración fílmica y deDubois y Parejo para las formas de inserción de los créditos. Los resultados muestran cuatro fórmulas que delatan la presencia de la fotografía en los títulos de crédito: el Time-lapse, lo profílmico, el congelado de imagen y la inserción de fotografías. Este último hace referencia a objetos reales, cuyos motivos visuales más recurrentes se corresponden con el collage, la fragmentación, el cromatismo artificioso, la repetición de contenidos, la simetría yla metáfora visual (que marca la relación de los créditos con los personajes y la narración fílmica).
Vida y muerte de la máquina de moler maíz: una investigación sobre los artefactos practicados
Authors: Mejía Amézquita Valentina , Zapata Arango Luisa Fernanda
Published: September 2022

Los artefactos son en la medida en que están incorporados en la vida del día a día, en las dinámicas de lo cotidiano que nos domestican y en las prácticas que nos reconocen como humanos miembros de una colectividad o cultura. Ahora, ¿qué sucede con los artefactos si las prácticas humanas mutan y la cotidianidad, ya sea a causa de este cambio o del olvido, se desdeñan? Esto requiere preguntarse, también, por los significados que se construyen tras la interacción entre sujetos y artefactos, por los rasgos que caracterizan a estos últimos en función de las identidades de un territorio y por las lógicas donde es posible ver lo que es vigente u obsolescente en las maneras de hacer1 en el camino a territorializar lo vital. Este artículo es resultado de una investigación que se ocupa de las formas de incorporación, práctica y olvido de los artefactos de la vida cotidiana, en particular, la máquina de moler maízen el contexto territorial de Riosucio, Colombia, a través de una apuesta teórico-hermenéutica que se vale de la hibridación entre los propósitos del diseño emergente y el diseño etnográfico, con el fin de poner en cuestión la dimensión diseñística de la tradición y obsolescencia de un artefacto, en clave territorial.
Extraordinary economy policies amid Covid-19 pandemic crisis: economic growth, labour productivity and elasticity of substitution
Authors: Ozkaya Ata
Published: September 2022

Purpose- This study investigates current financial, fiscal and monetary policies implemented to enhance growth rate in developed economies. First main theoretical findings of neoclassical growth theory are reconsidered. Second, current economy policies from the perspectives of Central banks and Treasury departments are analyzed. Finally, the relationship between these two is investigated and whether the policies are adequate to theoretical findings is examined.
Methodology- From the perspective of descriptive statistics, first; time evlotion of labor's share of output from 1947Q1 through 2016Q3 is analyzed. Second, time evolution of percentage change in labor productivity with respect to real hourly compensation are considered from 1948Q1 through 2022Q1. In addition, to identify the accelerating gap between labor productivity and compensation over recent decades, annual index levels from 1973 to 2022 for labor productivity with respect to real hourly compensation are taken into account. Third, the phase-space representation of rate of real growth for output per capita is developed. In methodological perspective, both time-space and phase-space analyses on output per capita, labor productivity and labor compensation clear the way to establish a theoretical model, which explains the interaction between these variables based on constant elasticity of substitution production function.
Findings- For case of elasticity of substitution lower-than-unity, the relationship between rate of real growth for marginal productivity and average productivity of labor is obtained and is used to enlighten current U.S. monetary and fiscal policy implementations.
Conclusion- The results demonstrate that amid Covid-19 pandemics, U.S. fiscal policy and monetary policy do not optimally match and hence the fiscal policy should be calibrated. U.S. fiscal policy increased minimum wages and U.S. monetary policy addressed tighter and perfectly competitive labor market. These two policies do not coincide in terms of efficiency. In other words, simultaneous application of these two policies will not give desired compound result.

Keywords: Economic growth, labor productivity, fiscal policy, labor compensation, monetary policy
JEL Codes: E62, O40, O41
The effects of airport slot allocation method on competition: Empirical analysis of competition through slots at JFK International Airport
Authors: Avci Cem , Ates Savas S.
Published: September 2022

Purpose- This study aims to indicate the effects of the current slot allocation method specified in the IATA Worldwide Slot Guidelines, which is used to allocate airport slots to airlines, on airline transport market concentration and competition.
Methodology- John F. Kennedy Airport (JFK), which allocates slots to airlines with the IATA method, was taken as a sample in the study. Airline’s JFK slot data obtained from the Federal Aviation Administration's Slot Administration Office were analysed with the Herfindahl-Hirschman Index (HHI) and the n-Firm Concentration Ratio (CRn).
Findings- According to the findings obtained from the analyses, it has been stated that the concentration in the JFK International Airport market is high and the competition is low. It has been determined that the majority of the slots are owned by 3 long-established US airlines using the airport as their base airport, and the remaining slots are shared by many airlines.
Conclusion- As a result of the study, it is revealed how the historical rights and pool system in the current slot allocation method affect concentration, competition, new entrants to the market and the power of new entrants to increase their shares.

Keywords: Airport slot, market concentration, competition, Herfindahl-Hirschman, CRn
JEL Codes: B22, D40, L93
Inspiration on strategy as practice from past to the present
Authors: Gurbuz Fatma Gulruh , Yener Mujdelen Ipek , Yukaripinar Sevde Nur , Huseyinzade Huseyin
Published: September 2022

Purpose- The goal of this study is to analyze the historical evolution, contributions, turning moments, and prospects of a creative movement called "Strategy As Practice".
Methodology- The methodology of this study is a thorough literature review of Strategy as Practice from past to the present.
Findings- There are several different sources of research on Strategy As Practice. The roots of Strategy As Practice research can be found in the classics of strategy process research as well as countless initiatives to widen and innovate strategic management. Strategy As Practice has just recently emerged as a well-defined area of study in the field of strategy research, uniting experts with similar viewpoints. Strategy As Practice was defined and published in a special issue of the Journal of Management Studies as "micro strategy and strategizing," and afterwards, its studies and research were featured in numerous significant publications.
Conclusion- Strategy As Practice has been the subject of many studies and presentations of various methodologies. However, it is crucial for future study that these studies are methodical or well-coordinated. The literature on Strategy as Practice needs recent studies that demonstrate how it has changed over time and offer guidance for upcoming study in this field.

Keywords: Roots of strategy, practice, praxis, practitioner, strategy as practice.
JEL Codes: M10, M16, M19
The effects of internet of things on the transportation cost management: a study of logistics company
Authors: Cakmak Mehmet , Ozerhan Yildiz
Published: September 2022

Purpose- The purpose of this study is to examine the Internet of Things (IoT) conceptually and structurally. In this regard, the study will examine the potential effects of the investments of the Internet of Things in the transportation operations of logistics, discuss the potential effects of the transportation costs of the Internet of Things and investments on control and Management. This study also analyze and evaluate such investments in a logistics company.
Methodology- In order to examine the potential effects of IoT investments on the management of transportation costs, an interview was conducted with an Istanbul-centered company of logistics service provider in this study. The data were collected and evaluated by asking open-ended questions within the scope of qualitative research with an interview technique.
Findings- It was determined that the company gained the advantage of real-time monitoring and controlling of the transportation operations, real-time monitoring of vehicles and drivers, monitoring of the thermal conditions of loads, monitoring and controlling of the incidents of losses and accidents through hardware and various technology like the Internet of Things (IoT) and integrated sensors to it. On the other hand, the study received comprehensive support of data from the company about the transportation process and the control of vehicles, loads, and drivers with IoT investments and the costs of transportation. Thus, the study obtained significant advantages for determining, calculating, and controlling costs. However, since IoT investments are new, and R & D operations for some integrated technologies continue in the company, the quantitative data that include cost advantages have not been formed yet. Therefore, a limited evaluation was conducted.
Conclusion- Technically, IoT is a technology that connects the vehicles in transportation operations in logistics with smart networks. IoT enables complete control and real-time monitoring for transportation operations, and it can decrease setbacks and waiting during the transportation process. In this regard, it can increase the management power for the transportation costs by offering advantageous qualities, such as comprehensive data support and real-time monitoring for determining and calculating the transportation costs and controlling expenses or spending. Hence, IoT can increase value-added for transportation operations and provide competitive pricing advantages with its cost. Consequently, IoT investments can provide advantages like “offering a transportation service with high value-added to supply chains, decreasing the costs of vehicles and drivers, and optimal pricing” to logistics companies against their opponents.

Keywords: Internet of things, transport operations, logistics cost, transportation cost, cost management.
JEL Codes: L90, L91, M10