Hasil untuk "Competition"

T. Soligard, M. Schwellnus, J. Alonso et al.

H. Feldman, Karl J. Friston

We suggested recently that attention can be understood as inferring the level of uncertainty or precision during hierarchical perception. In this paper, we try to substantiate this claim using neuronal simulations of directed spatial attention and biased competition. These simulations assume that neuronal activity encodes a probabilistic representation of the world that optimizes free-energy in a Bayesian fashion. Because free-energy bounds surprise or the (negative) log-evidence for internal models of the world, this optimization can be regarded as evidence accumulation or (generalized) predictive coding. Crucially, both predictions about the state of the world generating sensory data and the precision of those data have to be optimized. Here, we show that if the precision depends on the states, one can explain many aspects of attention. We illustrate this in the context of the Posner paradigm, using the simulations to generate both psychophysical and electrophysiological responses. These simulated responses are consistent with attentional bias or gating, competition for attentional resources, attentional capture and associated speed-accuracy trade-offs. Furthermore, if we present both attended and non-attended stimuli simultaneously, biased competition for neuronal representation emerges as a principled and straightforward property of Bayes-optimal perception.

L. Pessoa

Emotion and motivation have crucial roles in determining human behavior. Yet, how they interact with cognitive control functions is less understood. Here, the basic elements of a conceptual framework for understanding how they interact are introduced. More broadly, the 'dual competition' framework proposes that emotion and motivation affect both perceptual and executive competition. In particular, the anterior cingulate cortex is hypothesized to be engaged in attentional/effortful control mechanisms and to interact with several other brain structures, including the amygdala and nucleus accumbens, in integrating affectively significant signals with control signals in prefrontal cortex. An implication of the proposal is that emotion and motivation can either enhance or impair behavioral performance depending on how they interact with control functions.

S. Kastner, Leslie G. Ungerleider

R. Callaway, R. Brooker, P. Choler et al.

Hal L. Smith

C. Donald

Pasquale A. Marziliano, Maria F. Cataldo, Elisabetta Emo et al.

Mixed-species forests are increasingly promoted to improve forest functioning, yet their growth responses depend strongly on site conditions, stand structure, and management legacies, particularly in Mediterranean mountain environments. This study investigates how species mixture, stand structure, competition, and site conditions jointly influence tree growth and productivity in silver fir–beech forests of southern Italy. We combined stand-level indicators (current annual increment, recruitment period, structural diversity indices) with tree-level growth analyses based on basal area increment and linear mixed-effects models, comparing pure and mixed stands across three montane sites characterized by contrasting environmental conditions and management histories. Mixed stands showed higher productivity than monospecific stands, with increased current annual increment, shorter recruitment periods, and greater structural complexity. Linear mixed-effects modelling identified tree size, height, competition intensity, species identity, and stand mixture as key drivers of growth. Both species benefited from mixture, although silver fir showed a stronger positive response, with 12–15% higher Basal Area Increment (BAI) in mixed stands compared to pure stands, while beech gains were more moderate (5–8%). Structural diversity, quantified by Shannon and Gini indices, was markedly higher in mixed stands, indicating enhanced size differentiation and resource-use complementarity. Overall, the results demonstrate that productivity gains in silver fir–beech forests arise from the interaction between species mixture, stand structure, competition, and site-specific conditions. Species mixture enhances individual-tree growth primarily by modulating competitive interactions, with the magnitude of benefits varying across sites according to structural and management-related constraints. These findings provide quantitative support for site-adapted management strategies that promote mixed and structural diverse forests in Mediterranean mountain regions.

Cristóbal López, Eduardo H. Colombo, Emilio Hernández-García et al.

This chapter investigates some mechanisms behind pattern formation driven by competitive-only or repelling interactions, and explores how these patterns are influenced by different types of particle movement. Despite competition and repulsion are both anti-crowding interactions, collective effects may lead to clusters of individuals, which can arrange periodically. Through the analysis of two models, it provides insights into the similarities and differences in the patterns formed and underlines the role of movement in shaping the spatial distribution of biological populations.

Khalil Al Handawi, Fabian Bastin

The air transportation market is highly competitive and dynamic. Airlines often form alliances to expand their network reach, improve operational efficiency, and enhance customer experience. However, the impact of these alliances on market competition and operational efficiency is not fully understood. In this paper, we propose a novel approach to analyze airline alliances using multi\mfabian{-}attribute graph partitioning. We develop metrics to quantify the competitiveness of flight segments and the market penetration capability of airlines based on their alliance memberships. We formulate a bi\mfabian{-}objective optimization problem to maximize both competition and market penetration simultaneously. We also propose algorithms to solve this optimization problem and demonstrate their effectiveness using real-world flight schedule data. Our results provide insights into the structure of airline alliances and their implications for market competition and operational efficiency.

G. Parker

Angelica-Nicoleta NECULĂESEI (ONEA), Irina-Teodora MANOLESCU

Today's world comes with numerous challenges, especially in the educational space. New technologies and the virtual environment bring changes in values, attitudes, and behaviors, creating the premises for redefining the educational process on the one hand, and on the other hand, generating interest in the use of game elements in non-play contexts through gamification. The specialized literature supports this orientation by presenting the benefits and the problems that need to be addressed for better integration of gamification in university environments. One of the important issues highlighted is the need to adapt to cultural specificity, which is related to resistance to change, the nature of motivation, and the degree of appreciation for cooperation or competition, among other factors.

Fayong Zhang, Caixian Li, Rui Li et al.

Abstract This research is focused on addressing the energy-aware distributed heterogeneous welding shop scheduling (EADHWS) problem. Our primary objectives are to minimize the maximum finish time and total energy consumption. To accomplish this, we introduce a learning-based cooperative and competitive multi-objective optimization method, which we refer to as LCCMO. We begin by presenting a multi-rule cooperative initialization approach to create a population that combines strong convergence and diversity. This diverse population forms the foundation for our optimization process. Next, we develop a multi-level cooperative global search strategy that explores effective genes within solutions from different angles and sub-problems. This approach enhances our search for optimal solutions. Moreover, we design a competition and cooperation strategy for different populations to expedite convergence. This strategy encourages the exchange of information and ideas among diverse populations, thereby accelerating our progress. We also introduce a multi-operator cooperative local search technique, which investigates elite solutions from various directions, leading to improved convergence and diversity. In addition, we integrate Q-learning into our competitive swarm optimizer to explore different regions of the objective space, enhancing the diversity of the elite archive. Q-learning guides the selection of operators within the small-size population, contributing to more efficient optimization. To evaluate the effectiveness of LCCMO, we conduct numerical experiments on 20 instances. The experimental results unequivocally demonstrate that LCCMO outperforms six state-of-the-art algorithms. This underscores the potential of our learning and knowledge-driven evolutionary framework in enhancing performance and autonomy when it comes to solving EADHWS.

Niklas Kochdumper, Youran Wang, Johannes Betz et al.

In recent years, different approaches for motion planning of autonomous vehicles have been proposed that can handle complex traffic situations. However, these approaches are rarely compared on the same set of benchmarks. To address this issue, we present the results of a large-scale motion planning competition for autonomous vehicles based on the CommonRoad benchmark suite. The benchmark scenarios contain highway and urban environments featuring various types of traffic participants, such as passengers, cars, buses, etc. The solutions are evaluated considering efficiency, safety, comfort, and compliance with a selection of traffic rules. This report summarizes the main results of the competition.

Boyang Li, Xinyi Ying, Ruojing Li et al.

In this paper, we briefly summarize the first competition on resource-limited infrared small target detection (namely, LimitIRSTD). This competition has two tracks, including weakly-supervised infrared small target detection (Track 1) and lightweight infrared small target detection (Track 2). 46 and 60 teams successfully registered and took part in Tracks 1 and Track 2, respectively. The top-performing methods and their results in each track are described with details. This competition inspires the community to explore the tough problems in the application of infrared small target detection, and ultimately promote the deployment of this technology under limited resource.

Teddy Mekonnen, Bobak Pakzad-Hurson

An agent engages in sequential search and learns about the quality of sampled goods through signals purchased from profit-maximizing information broker(s). We study how the market structure--the number of competing brokers--shapes the pricing and design of information, as well as the resulting welfare outcomes. We characterize the equilibrium payoff set, and show that when the agent's search cost falls below a threshold, market structure affects neither how much surplus is generated in equilibrium nor how it is divided. Above this threshold, however, competition yields equilibrium outcomes that raise the agent's payoff but reduce total surplus relative to any monopoly equilibrium outcome. Methodologically, we extend the classic theory of repeated games to stopping problems, such as sequential search.

Shimelis Tamirat, Chalchissa Amentie

AbstractIn contemporary dynamic and turbulent competitive business landscape, knowledge-based competition became a new normal. So far, studies gave little attention to an integration of knowledge and dynamic capabilities for business strategies, however. Therefore, this study was initiated to see recent literature developments in knowledge-based dynamic capabilities (KBDCs) as juxtaposition of both themes to identify foundational sources, factors impacting, and consequences by conducting a systematic review. The review considered 72 empirical papers published from 1 January 2015 to 19 July 2022. The findings indicated that tacit knowledge resource, knowledge management, managerial features (team composition, technological insight, and tenure), intellectual/human capital, organizational design/structure, financial resources, social capital, technology ownership and usage, existing operational and dynamic capabilities, and firm location are the foundations of KBDCs. Contextual factors affecting KBDCs at corporate interior are namely firm size, type, realized absorptive capacity, and experiential and organizational knowledge. Those external factors are new technologies, global competition, market dynamism, local business ecosystem, public innovation intermediaries, economic circumstances, and regulatory factors. Businesses used KBDCs’ gained sustainable competitive advantage, improvement in resource base, and proficient in firm’s business performance. Theoretical contributions, implications to practitioners, and future lines of research were discussed.

Nick Doty, Mallory Knodel

The principles of net neutrality have been essential for maintaining the diversity of services built on top of the internet and for maintaining some competition between small and large providers of those online services. That diversity and competition, in turn, provide users with a broader array of choices for seeking online content and disseminating their own speech. Furthermore, in order for the internet to be used to its full potential and to protect the human rights of internet users, we need privacy from surveillance and unwarranted data collection by governments, network providers, and edge providers. The transition to 5G mobile networks enables network operators to engage in a technique called network slicing. The portion of a network that is sliced can be used to provide a suite of different service offerings, each tailored to specific purposes, instead of a single, general-purpose subscription for mobile voice and data. This requires a careful approach. Our report describes the technologies used for network slicing and outlines recommendations -- for both operators and regulators -- to enable network slicing while maintaining network neutrality, protecting privacy, and promoting competition.

Pei-Sen Li, Jian Wang, Xiaowen Zhou

We study quasi-stationary distribution of the continuous-state branching process with competition introduced in Berestycki, Fittipaldi and Fontbona\ (Probab. Theory Relat. Fields, 2018). This process is constructed as the unique strong solution to a stochastic integral equation with jumps. An important example is the logistic branching process constructed in Lambert (Ann. Appl. Probab., 2005). We establish the strong Feller property,trajectory Feller property, Lyapunov condition, weak Feller property and irreducibility, respectively. These properties together allow us to prove that when the competition term is strong enough near $+\infty$, then there is a unique quasi-stationary distribution, which attracts all initial distributions with exponential rates.

Sven Behnke, Julie A. Adams, David Locke

The $10M ANA Avatar XPRIZE aimed to create avatar systems that can transport human presence to remote locations in real time. The participants of this multi-year competition developed robotic systems that allow operators to see, hear, and interact with a remote environment in a way that feels as if they are truly there. On the other hand, people in the remote environment were given the impression that the operator was present inside the avatar robot. At the competition finals, held in November 2022 in Long Beach, CA, USA, the avatar systems were evaluated on their support for remotely interacting with humans, exploring new environments, and employing specialized skills. This article describes the competition stages with tasks and evaluation procedures, reports the results, presents the winning teams' approaches, and discusses lessons learned.