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Artykuły w czasopismach na temat "Dynamic agent ordering"
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Hammoujan, Saida, Imade Benelallam i El Houssine Bouyakhf. "Dynamic vs. static agent ordering in distributed arc consistency". International Journal of Advanced Intelligence Paradigms 10, nr 3 (2018): 266. http://dx.doi.org/10.1504/ijaip.2018.090790.
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Bouyakhf, El Houssine, Saida Hammoujan i Imade Benelallam. "Dynamic vs. static agent ordering in distributed arc consistency". International Journal of Advanced Intelligence Paradigms 10, nr 3 (2018): 266. http://dx.doi.org/10.1504/ijaip.2018.10011381.
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ZHANG, YIFENG, SIDDHARTHA BHATTACHARYYA i XIAOMING LI. "FROM CHOICE OF PROCUREMENT STRATEGY TO SUPPLY NETWORK CONFIGURATION: AN EVOLUTIONARY APPROACH". International Journal of Information Technology & Decision Making 09, nr 01 (styczeń 2010): 145–73. http://dx.doi.org/10.1142/s0219622010003671.
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This study examines the complex and evolutionary nature of supply network configuration. Taking a bottom-up approach, we examine how supply network configuration at the macro-level evolves as a result of individual retailers' dynamic choice of procurement strategies at the micro-level. Employing agent-based modeling, we focus on the effects of switch cost and distributors' ordering policy on the evolution of supply network configuration. Our results show that (1) supply networks tend to evolve into a set of separate supply chains when switch cost is high and into an integrated network when switch cost is low, (2) a responsive ordering policy adopted by distributors is more conducive to the integrated network configuration than a non-responsive policy, and (3) lack of coordination among retailers in their dynamic choice of procurement strategies hurts not only the overall system performance, but also retailers themselves. More importantly, our study demonstrates the capabilities of agent-based modeling as a methodology for researching complex supply network issues.
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Hu, Shuli, Daniel D. Harabor, Graeme Gange, Peter J. Stuckey i Nathan R. Sturtevant. "Multi-Agent Path Finding with Temporal Jump Point Search". Proceedings of the International Conference on Automated Planning and Scheduling 32 (13.06.2022): 169–73. http://dx.doi.org/10.1609/icaps.v32i1.19798.
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Temporal Jump Point Search (JPST) is a recently introduced algorithm for grid-optimal pathfinding among dynamic temporal obstacles. In this work we consider JPST as a low-level planner in Multi-Agent Path Finding (MAPF). We investigate how the canonical ordering of JPST can negatively impact MAPF performance and we consider several strategies which allow us to overcome these limitations. Experiments show our new CBS/JPST approach can substantially improve on CBS/SIPP, a contemporary and leading method from the area.
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Yang, Ning, Yingzi Ding, Junge Leng i Lei Zhang. "Supply Chain Information Collaborative Simulation Model Integrating Multi-Agent and System Dynamics". Promet 34, nr 5 (30.09.2022): 711–24. http://dx.doi.org/10.7307/ptt.v34i5.4092.
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Supply chain collaboration management is a systematic, integrated and agile advanced management mode, which helps to improve the competitiveness of enterprises and the entire supply chain. In order to realise the synergy of supply chain, the most important is to realise the dynamic synergy of information. Here we proposed a strategy to integrate system dynamics and multi-agent system modelling methods. Based on the strategy of supply chain information sharing and coordination, a two-level aggregation hybrid model was designed and established. Through the computer simulation analysis of the two modes before and after information collaboration, it is found that under the information collaboration mode, the change trend of order or inventory of suppliers and manufacturers always closely matches that of retailers. After the implementation of supply chain information coordination, ordering and inventory can be reasonably planned and matched, and problems such as over-stocking or short-term failure to meet order demands caused by poor information communication will no longer occur, which can greatly reduce the “bullwhip effect”.
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Banerjee, Bikramjit, Landon Kraemer i Jeremy Lyle. "Multi-Agent Plan Recognition: Formalization and Algorithms". Proceedings of the AAAI Conference on Artificial Intelligence 24, nr 1 (4.07.2010): 1059–64. http://dx.doi.org/10.1609/aaai.v24i1.7746.
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Multi-Agent Plan Recognition (MAPR) seeks to identify the dynamic team structures and team behaviors from the observations of the activity-sequences of a set of intelligent agents, based on a library of known team-activities (plan library). It has important applications in analyzing data from automated monitoring, surveillance, and intelligence analysis in general. In this paper, we formalize MAPR using a basic model that explicates the cost of abduction in single agent plan recognition by "flattening" or decompressing the (usually compact, hierarchical) plan library. We show that single-agent plan recognition with a decompressed library can be solved in time polynomial in the input size, while it is known that with a compressed (by partial ordering constraints) library it is NP-complete. This leads to an important insight: that although the compactness of the plan library plays an important role in the hardness of single-agent plan recognition (as recognized in the existing literature), that is not the case with multiple agents. We show, for the first time, that MAPR is NP-complete even when the (multi-agent) plan library is fully decompressed. As with previous solution approaches, we break the problem into two stages: hypothesis generation and hypothesis search. We show that Knuth's ``Algorithm X'' (with the efficient ``dancing links'' representation) is particularly suited for our model, and can be adapted to perform a branch and bound search for the second stage, in this model. We show empirically that this new approach leads to significant pruning of the hypothesis space in MAPR.
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Blázquez-Blázquez, Enrique, Rosa Barranco-García, Tamara M. Díez-Rodríguez, María L. Cerrada i Ernesto Pérez. "Combined Effects from Dual Incorporation of ATBC as Plasticizer and Mesoporous MCM-41 as Nucleating Agent on the PLA Isothermal Crystallization in Environmentally-Friendly Ternary Composite Systems". Polymers 15, nr 3 (25.01.2023): 624. http://dx.doi.org/10.3390/polym15030624.
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Different materials, based on an L-rich polylactide (PLA) as matrix, acetyl tri-n-butyl citrate (ATBC) as plasticizer, and mesoporous Mobile Crystalline Material.41 (MCM-41) particles as nucleating agent, were attained by melt extrusion. These materials are constituted by (a) binary blends of PLA and ATBC with different contents of the latest; (b) a dual compound of PLA and a given amount of MCM-41 silica (5 wt.%); and (c) ternary composites that include PLA, ATBC at several compositions and mesoporous MCM-41 at 5 wt.%. Influence of the incorporation of the plasticizer and nucleating particles has been comprehensively analyzed on the different phase transitions: glass transition, cold crystallization, melt crystallization and melting processes. Presence of both additives moves down the temperature at which PLA phase transitions take place, while allowing the PLA crystallization from the melt at 10 °C/min in the composites. This tridimensional ordering is not noticeable in the pristine PLA matrix and, accordingly, PLA crystallization rate is considerably increased under dynamic conditions and also after isothermal crystallization from either the melt or the glassy state. An important synergistic effect of dual action of ATBC and MCM-41 has been, therefore, found.
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Clarke, Sharon E., Manojkumar Saranathan, Dan W. Rettmann, Brian A. Hargreaves i Shreyas S. Vasanawala. "High resolution multi-arterial phase MRI improves lesion contrast in chronic liver disease". Clinical & Investigative Medicine 38, nr 3 (31.05.2015): 90. http://dx.doi.org/10.25011/cim.v38i3.22704.
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Purpose: To determine the reliability of arterial phase capture and evaluate hypervascular lesion contrast kinetics with a combined view-sharing and parallel imaging dynamic contrast-enhanced acquisition, DIfferential Sub-sampling with Cartesian Ordering (DISCO), in patients with known chronic liver disease. Methods: A retrospective review of 3T MR images from 26 patients with known chronic liver disease referred for hepatocellular carcinoma surveillance or post-treatment follow up was performed. After administration of a gadolinium-based contrast agent, a multiphasic acquisition was obtained in a 28 s breath-hold, from which seven sequential post-contrast image volumes were reconstructed. Results: The late arterial phase was successfully captured in all cases (26/26, 95% CI 87-100%). Images obtained 26 s post-injection had the highest frequency of late arterial phase capture (20/26) and lesion detection (23/26) of any individual post-contrast time; however, the multiphasic data resulted in a significantly higher frequency of late arterial phase capture (26/26, p=0.03) and a higher relative contrast (5.37+/-0.97 versus 7.10+/-0.98, p < 0.01). Conclusion: Multiphasic acquisition with combined view-sharing and parallel imaging reliably captures the late arterial phase and provides sufficient temporal resolution to characterize hepatic lesion contrast kinetics in patients with chronic liver disease while maintaining high spatial resolution.
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Wang, Mengying, Angélica Luana C. Barra, Hévila Brognaro i Christian Betzel. "Exploring Nucleation Pathways in Distinct Physicochemical Environments Unveiling Novel Options to Modulate and Optimize Protein Crystallization". Crystals 12, nr 3 (21.03.2022): 437. http://dx.doi.org/10.3390/cryst12030437.
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The scientific discussion about classical and nonclassical nucleation theories has lasted for two decades so far. Recently, multiple nucleation pathways and the occurrence and role of metastable intermediates in crystallization processes have attracted increasing attention, following the discovery of functional phase separation, which is now under investigation in different fields of cellular life sciences, providing interesting and novel aspects for conventional crystallization experiments. In this context, more systematic investigations need to be carried out to extend the current knowledge about nucleation processes. In terms of the data we present, a well-studied model protein, glucose isomerase (GI), was employed first to investigate systematically the early stages of the crystallization process, covering condensing and prenucleation ordering of protein molecules in diverse scenarios, including varying ionic and crowding agent conditions, as well as the application of a pulsed electric field (pEF). The main method used to characterize the early events of nucleation was synchronized polarized and depolarized dynamic light scattering (DLS/DDLS), which is capable of collecting the polarized and depolarized component of scattered light from a sample suspension in parallel, thus monitoring the time-resolved evolution of the condensation and geometrical ordering of proteins at the early stages of nucleation. A diffusion interaction parameter, KD, of GI under varying salt conditions was evaluated to discuss how the proportion of specific and non-specific protein–protein interactions affects the nucleation process. The effect of mesoscopic ordered clusters (MOCs) on protein crystallization was explored further by adding different ratios of MOCs induced by a pEF to fresh GI droplets in solution with different PEG concentrations. To emphasize and complement the data and results obtained with GI, a recombinant pyridoxal 5-phosphate (vitamin B6) synthase (Pdx) complex of Staphylococcus aureus assembled from twelve monomers of Pdx1 and twelve monomers of Pdx2 was employed to validate the ability of the pEF influencing the nucleation of complex macromolecules and the effect of MOCs on adjusting the crystallization pathway. In summary, our data revealed multiple nucleation pathways by tuning the proportion of specific and non-specific protein interactions, or by utilizing a pEF which turned out to be efficient to accelerate the nucleation process. Finally, a novel and reproducible experimental strategy, which can adjust and facilitate a crystallization process by pEF-induced MOCs, was summarized and reported for the first time.
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Timuri, Timor, Pieter Spronck i Jaap Van den Heri. "Automatic Rule Ordering for Dynamic Scripting". Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 3, nr 1 (29.09.2021): 49–54. http://dx.doi.org/10.1609/aiide.v3i1.18782.
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The goal of adaptive game AI is to enhance computer-controlled game-playing agents with (1) the ability to self-correct mistakes, and (2) creativity in responding to new situations. Dynamic scripting is a reinforcement learning technique that realises fast and reliable online adaptation of game AI. It employs knowledge bases which contain rules that can be included in game scripts. To be successful, dynamic scripting requires a mechanism to order the rules that are selected for scripts. So far, rule ordering was achieved by a manually-tuned priority value for each rule. In the present research, we propose three mechanisms to order rules automatically for dynamic scripting. We performed experiments in which we let dynamic scripting, using each of the three mechanisms, play against manually-designed tactics. Our results show that dynamic scripting with automatic rule ordering generates game AI that is at least as effective as dynamic scripting with manually-tuned priority values. Moreover, it has the ability to generate novel game AI with significantly increased effectiveness. The costs are a slight decrease in learning efficiency. So, we may conclude that automatic rule ordering is a valuable enhancement for dynamic scripting.
Rozprawy doktorskie na temat "Dynamic agent ordering"
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Zhou, Lingzhong, i n/a. "Agent Ordering and Nogood Repairs in Distributed Constraint Solving". Griffith University. School of Information and Communication Technology, 2006. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20070713.162515.
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The distributed constraint satisfaction problem is a general formalization used to represent problems in distributed multi-agent systems. A large body of problems in artificial intelligence and computer science can be easily formulated as distributed constraint satisfaction problems. In this thesis we study agent ordering, effects of no-goods, search efficiency and threshold repairing in distributed constraint satisfaction problems and its variants. A summary of contributions is as follows: 1. We present a new algorithm, Dynamic Agent Ordering. A distinctive feature of this algorithm is that it uses the degree of unsatisfiability as a guiding parameter to dynamically determine agent ordering during the search. We show through an empirical study that our algorithm performs better than the existing approaches. In our approach, the independence of agents is guaranteed and agents without neighbouring relationships can run concurrently and asynchronously. (Part of this work was published in the Australian Al Conference (80)). 2. We extend the Dynamic Agent Ordering algorithm by incorporating a novel technique called nogood repairing. This results in a dramatic reduction in the nogoods being stored, and communication costs. In an empirical study, we11 show that this approach outperforms an equivalent static ordering algorithm and a current state-of-the-art technique in terms of execution time, memory usage and communication cost. (Part of this work was published at FLAIRS Conference (81)). Further, we introduce a new algorithm, Over-constrained Dynamic Agent Ordering, that breaks new ground in handling multiple variables per agent in distributed over-constrained satisfaction problems. The algorithm also uses the degree of unsatisfiability as a measure for relaxing constraints, and hence as a way to guide the search toward the best optimal solution(s). By applying our Threshold Repair method, we can solve a distributed constraint satisfaction problem without knowing whether the problem is under- or over-constrained. In an experimental study, we show that the new algorithm compares favourably to an implementation of asynchronous weak commitment search adapted to handle over-constrained problems. (Part of this work was published at the Canadian AI conference (79)).
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Zhou, Lingzhong. "Agent Ordering and Nogood Repairs in Distributed Constraint Solving". Thesis, Griffith University, 2006. http://hdl.handle.net/10072/365303.
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The distributed constraint satisfaction problem is a general formalization used to represent problems in distributed multi-agent systems. A large body of problems in artificial intelligence and computer science can be easily formulated as distributed constraint satisfaction problems. In this thesis we study agent ordering, effects of no-goods, search efficiency and threshold repairing in distributed constraint satisfaction problems and its variants. A summary of contributions is as follows: 1. We present a new algorithm, Dynamic Agent Ordering. A distinctive feature of this algorithm is that it uses the degree of unsatisfiability as a guiding parameter to dynamically determine agent ordering during the search. We show through an empirical study that our algorithm performs better than the existing approaches. In our approach, the independence of agents is guaranteed and agents without neighbouring relationships can run concurrently and asynchronously. (Part of this work was published in the Australian Al Conference (80)). 2. We extend the Dynamic Agent Ordering algorithm by incorporating a novel technique called nogood repairing. This results in a dramatic reduction in the nogoods being stored, and communication costs. In an empirical study, we11 show that this approach outperforms an equivalent static ordering algorithm and a current state-of-the-art technique in terms of execution time, memory usage and communication cost. (Part of this work was published at FLAIRS Conference (81)). Further, we introduce a new algorithm, Over-constrained Dynamic Agent Ordering, that breaks new ground in handling multiple variables per agent in distributed over-constrained satisfaction problems. The algorithm also uses the degree of unsatisfiability as a measure for relaxing constraints, and hence as a way to guide the search toward the best optimal solution(s). By applying our Threshold Repair method, we can solve a distributed constraint satisfaction problem without knowing whether the problem is under- or over-constrained. In an experimental study, we show that the new algorithm compares favourably to an implementation of asynchronous weak commitment search adapted to handle over-constrained problems. (Part of this work was published at the Canadian AI conference (79)).Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Information and Communication Technology
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Części książek na temat "Dynamic agent ordering"
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Zhou, Lingzhong, John Thornton i Abdul Sattar. "Dynamic Agent Ordering in Distributed Constraint Satisfaction Problems". W Lecture Notes in Computer Science, 427–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-24581-0_36.
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Bader, Ralf M. "Agent-Relative Prerogatives and Suboptimal Beneficence". W Oxford Studies in Normative Ethics Volume 9, 223–50. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198846253.003.0011.
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The first part of Chapter 11 uses considerations of sequential choice to argue that suboptimal beneficence is impermissible. The second part shows how the prohibition on suboptimal beneficence follows from an agent-relative theory that understands permissible actions in terms of a dominance principle defined over both the agent-relative and the agent-neutral ordering. This theory incorporates agent-relative prerogatives that ensure that agents are not required to do what is impartially best, yet rules out suboptimal beneficence. The third part shows that the prohibition on suboptimal beneficence is in tension with dynamic consistency, since it leads to violations of expansion consistency condition BETA. If an agent makes use of myopic choice principles (which are purely forward-looking) or sophisticated choice principles (that make use of backwards induction), then there can be cases in which he can, by means of a sequence of permissible choices, bring about an outcome that is deemed to be impermissible from the outset. This problem is addressed by developing global choice principles that ensure dynamic consistency.