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Open Contractible Global Constraints

Michael J. Maher
2009 International Joint Conference on Artificial Intelligence  
However, in general, filtering that is sound for a global constraint can be unsound when the constraint is open.  ...  Open forms of global constraints allow the addition of new variables to an argument during the execution of a constraint program.  ...  Recent work has focused on supporting open versions of global constraints.  ... 
dblp:conf/ijcai/Maher09 fatcat:wkr66ed3vrbxjhfywsyozyk7kq

Constraint Satisfaction as Global Optimization

Pedro Meseguer, Javier Larrosa
1995 International Joint Conference on Artificial Intelligence  
We present a optimization formulation for discrete binary CSP, based on the construction of a continuous function A(P) whose global maximum represents the best possible solution for that problem.  ...  We have tested this heuristic with forward checking on several classes of CSP.  ...  When possible, this issue is solved looking for a local maximum satisfying an additional condition which guarantees that it is a global one.  ... 
dblp:conf/ijcai/MeseguerL95 fatcat:jozlsnehqrbn3m3kpwdusoehri

Belief Change Based on Global Minimisation

James P. Delgrande, Jérôme Lang, Torsten Schaub
2007 International Joint Conference on Artificial Intelligence  
We report on experiments in the context of discovering links in real biological networks, a demonstration of the practical usefulness of the approach. * Recently moved to the Katholieke Universiteit Leuven  ...  In addition, they often impose various constraints on probabilities.  ...  One basic approach relies on the inclusion-exclusion principle from set theory. It requires the computation of conjunctive probabilities of all sets of conjunctions appearing in the DNF formula.  ... 
dblp:conf/ijcai/DelgrandeLS07 fatcat:lgjuq2ob3fb3vgb2qakssumjfi

Table of Contents

2020 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)  
Intelligence for Managing IoT Enabled Houseplants Antti Nurminen (Aalto University, Finland, Finland), Avleen Malhi (Aalto University, Finland) 78 Technological Solution Development During the COVID  ...  National Tsing-Hua University, Taiwan), Ren-Song Tsay (National Tsing-Hua University, Taiwan) 71 Machine Learning in IoT AI and IoT IoT Applications: From Theory to Practice Green Thumb Engineering: Artificial  ... 
doi:10.1109/gcaiot51063.2020.9345897 fatcat:wwh25qskdba4xcsp5vpq2wfmwq

Table of Contents

2021 2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)  
United Arab Emirates), Hesham El-Sayed (United Arab Emirates University, United Arab Emirates), Manzoor Khan (UAE University, United Arab Emirates), Muhammad J Khan (United Arab Emirates Performance Study on  ... 
doi:10.1109/gcaiot53516.2021.9692937 fatcat:w5o53cwovza3xlfsa5ecatzey4

Global/Local Dynamic Models

Avi Pfeffer, Subrata Das, David Lawless, Brenda Ng
2007 International Joint Conference on Artificial Intelligence  
In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself.  ...  We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics.  ...  Global/local PF is based on the principle of reasoning globally about global dynamics and locally about local dynamics.  ... 
dblp:conf/ijcai/PfefferDLN07 fatcat:tjya6zd7lzbx5msodw5zphw2ti

MMA: Multi-Camera Based Global Motion Averaging

Hainan Cui, Shuhan Shen
2022 AAAI Conference on Artificial Intelligence  
In order to fully perceive the surrounding environment, many intelligent robots and self-driving cars are equipped with a multi-camera system.  ...  Experiments demonstrate that our algorithm achieves superior accuracy and robustness on various data sets compared to the state-of-the-art methods.  ...  By equipping our system, both selfdriving cars and intelligent robots can better perceive the surrounding environment.  ... 
dblp:conf/aaai/CuiS22 fatcat:kb3fh3uyjjcvnl3ljbwp732lam

Papers By Title

2021 2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)  
for IoT Applications Machine Learning Stacking Ensemble Model for Predicting Heart Attacks Mobility-As-A-Service Challenges and Opportunities in the Post-PandemicMulti-Agent Reinforcement Learning for Intelligent  ... 
doi:10.1109/gcaiot53516.2021.9693005 fatcat:rxr6i3xtgvbgjbcrbiymhjqiqa

On the Kernelization of Global Constraints

Clément Carbonnel, Emmanuel Hebrard
2017 Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence  
We showcase the theoretical interest of our ideas on two constraints, VertexCover and EdgeDominatingSet.  ...  Building on recent results for the VertexCover constraint, we introduce novel "loss-less" kernelization variants that are tailored for constraint propagation.  ...  Moreover, they rely on so-called propagation algorithms, one for each (global) constraint to prune the search space by reducing the domains.  ... 
doi:10.24963/ijcai.2017/81 dblp:conf/ijcai/CarbonnelH17 fatcat:sydskmscbjfaffcpieokmvkq6i

Numerica: A Modeling Language for Global Optimization

Pascal Van Hentenryck
1997 International Joint Conference on Artificial Intelligence  
What distinguishes the constraint-solving algorithm of NUMERICA is the combination of techniques from numerical analysis and artificial intelligence to obtain effective pruning techniques (for many problems  ...  There is no way to collect global information on a function by probing finitely many points.  ... 
dblp:conf/ijcai/Hentenryck97 fatcat:yrz2ffiy7rdetngq3azwspfalq

Artificial intelligence in human resource management in the Global South

Nir Kshetri
2020 Americas Conference on Information Systems  
The purpose of this paper is to examine the use of artificial intelligence (AI) in human resource management (HRM) in the Global South.  ...  AI deployment in HRM also has a potentially positive impact on the development, retainment and productive utilization of employees.  ...  Introduction Artificial intelligence (AI) is a potentially transformative force that is likely to change the role of management and organizational practices.  ... 
dblp:conf/amcis/Kshetri20 fatcat:6bcibbmdd5hrfmh2x763h5reb4

Emerging Architectures for Global System Science

Michela Milano, Pascal Van Hentenryck
2015 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
This paper addresses emergent architectures enabling controlling, predicting and reaoning on these systems.  ...  Our society is organized around a number of (interdependent) global systems.  ...  Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence  ... 
doi:10.1609/aaai.v29i1.9771 fatcat:rgv6uctyq5gcvdqe7wkhvgcsqe

Global Greedy Dependency Parsing

Zuchao Li, Hai Zhao, Kevin Parnow
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Most syntactic dependency parsing models may fall into one of two categories: transition- and graph-based models.  ...  The proposed global greedy parser only uses two arc-building actions, left and right arcs, for projective parsing.  ...  Our global greedy parser significantly outperforms the easy-first parser in(Kiperwasser and Goldberg 2016a) (HT-LSTM) on both PTB and CTB.  ... 
doi:10.1609/aaai.v34i05.6348 fatcat:ccww2n4vgrhtfhmbwd4wbaydb4

Global Model Checking on Pushdown Multi-Agent Systems

Taolue Chen, Fu Song, Zhilin Wu
2016 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
The algorithm is based on the saturation method, and is the first global model checking algorithm with a matching lower bound.  ...  We propose an exponential-time global model checking algorithm which extends similar algorithms for pushdown systems and modal mu-calculus.  ...  For each configuration p ⊥ , γω of P , λ ( p ⊥ Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence We could also prove the lower bound by a more involved reduction from the  ... 
doi:10.1609/aaai.v30i1.10124 fatcat:awezyvhqyvdodmmc2vkm5kfd4i

A Soft Global Precedence Constraint

David Lesaint, Deepak Mehta, Barry O'Sullivan, Luis Quesada, Nic Wilson
2009 International Joint Conference on Artificial Intelligence  
For this purpose, we present the global constraint SOFTPREC. Enforcing Generalized Arc Consistency (GAC) on SOFT-PREC is NP-complete.  ...  Therefore, we approximate GAC based on domain pruning rules that follow from the semantics of SOFTPREC; this pruning is polynomial.  ...  All these consistency techniques enforce bounds consistency on the objective variable v. The SoftPrec Global Constraint Let F, H, P, w be a feature subscription.  ... 
dblp:conf/ijcai/LesaintMOQW09 fatcat:wd3gt5foz5e5rmsnyclrnsg3wy
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