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Chasing Ghosts: Competing with Stateful Policies [article]

Uriel Feige, Tomer Koren, Moshe Tennenholtz
2014 arXiv   pre-print
In fact, in this setting it is impossible for the algorithm to estimate which policy gives the highest (or even approximately highest) total reward.  ...  If either the reference policies are stateless rather than stateful, or the feedback includes the rewards of all actions (the so called "expert" setting), previous work shows that the optimal regret grows  ...  Finally, we define an algorithm Afor the hidden bandit problem, based on A.  ... 
arXiv:1407.7635v1 fatcat:2hqvbcokbndabjtoahjbrpb25y

Higher-spin kinematics no ghosts on quantum space-time in Yang-Mills matrix models [article]

Harold C. Steinacker
2021 arXiv   pre-print
A classification of bosonic on- and off-shell modes on a cosmological quantum space-time solution of the IIB matrix model is given, which leads to a higher-spin gauge theory.  ...  In particular, the no-ghost-theorem is established.  ...  Skvortsov for useful discussions, and I am grateful to E. Delay and W. Schlag for pointing me to the appropriate mathematical literature.  ... 
arXiv:1910.00839v2 fatcat:mersk7xdjbchhnvzh54uefw5w4

Toward accurate real-time marker labeling for live optical motion capture

Shihong Xia, Le Su, Xinyu Fei, Han Wang
2017 The Visual Computer  
The key idea is to formulate the problem in a combinatorial optimization framework.  ...  This paper presents a novel accurate real-time online marker labeling algorithm for simultaneously dealing with missing and ghost markers.  ...  creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a  ... 
doi:10.1007/s00371-017-1400-y fatcat:dxavheew5fh3tjpitq7scnk6je

Applied Graph Theory to Real Smart City Logistic Problems

Jose M. Gutierrez, Michael Jensen, Tahir Riaz
2016 Procedia Computer Science  
We present a feasible solution for the non-trivial problem of planning routes, guaranteeing 100% coverage of the 19.000 km of roads in the Region and having hard computational time constrains.  ...  This paper provides an overview of the system designed for carrying out the project, focusing on the solution for the logistics problem presenting well-defined challenges.  ...  B) Evolutionary algorithms such a Genetic Algorithms or Simulated Annealing [13] are good options for solving combinatorial optimization problems in logistics, obtaining near optimal solutions in a relatively  ... 
doi:10.1016/j.procs.2016.09.291 fatcat:vi7ogyl2sjea7ll2jmc6a4utf4

Scheduling an Industrial Production Facility [chapter]

Eyjolfur Asgeirsson, Jonathan Berry, Cynthia A. Phillips, David J. Phillips, Cliff Stein, Joel Wein
2004 Lecture Notes in Computer Science  
- Schedule the jobs in the order given by C P j , respecting release dates.General Framework 1. Solve a relaxation of the given problem in order to obtain an ordering on the jobs.2.  ...  Our IP framework • IP -used both CPLEX and PICO (parallel integer combinatorial opti- mizer) [Eskstein,Phillips,Hart 2000] developed at Sandia and RUTCOR.  ...  For the most challenging series A problems (120 jobs and above), CPLEX and PICO both couldn't solve in a specified time limit (¿ 48 hours).  ... 
doi:10.1007/978-3-540-25960-2_9 fatcat:hr5ippq55vhddays5zgzmfds3q

Pac-mAnt: Optimization based on ant colonies applied to developing an agent for Ms. Pac-Man

Martin Emilio, Martinez Moises, Recio Gustavo, Saez Yago
2010 Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games  
This paper proposes the use of an optimization algorithm based on ant colonies for the development of competitive agents in the game environment in real time, specifically for the Ms.  ...  Furthermore, a genetic algorithm is implemented to optimize the parameters of the artificial ants. The best agent obtained through experimentation will be sent to the competition of Ms. Pac-Man  ...  AGENT DESIGN Optimization algorithms inspired by ant colonies (Ant Colony Optimization, ACO) have been successfully applied to a wide variety of combinatorial optimization problems.  ... 
doi:10.1109/itw.2010.5593319 dblp:conf/cig/MartinMRS10 fatcat:wbber4p4tnhethcsawddv24lsq

Combinatorial clustering and Its Application to 3D Polygonal Traffic Sign Reconstruction From Multiple Images

B. Vallet, B. Soheilian, M. Brédif
2014 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
We present a methodology to solve the resulting combinatorial optimization problem with some simplifications and approximations in order to make it tractable.  ...  This paper formulates a framework to use the geometric quality of the reconstruction as a hint to do a proper clustering.  ...  Top: a greedy heuristic generates a "ghost" 3D signs at C when reconstructing the real signs A and B.  ... 
doi:10.5194/isprsannals-ii-3-165-2014 fatcat:sum4cmvfyjaffae3zyatnc7jh4

Decision Making Agent Searching for Markov Models in Near-Deterministic World [article]

Gabor Matuz, Andras Lorincz
2011 arXiv   pre-print
We propose a learning architecture that utilizes combinatorial policy optimization to overcome non-Markovity and to develop efficient behaviors, which are easy to inherit, tests the Markov property of  ...  Thus, a learning agent -born with a representation and a policy- might wish to investigate to what extent the Markov property holds.  ...  CEM can be extended to online optimization [28] , which may suit real world RL problems better.  ... 
arXiv:1102.5561v2 fatcat:nmbhk2fqcfa4pbjdlvmeebwh5y

The random field Ising model : algorithmic complexity and phase transition

J.C. Angles d'Auriac, M. Preissmann, R. Rammal
1985 Journal de Physique Lettres  
We prove that finding a ground state of the ferromagnetic RFIM is a polynomial (P) optimization problem in any dimension d.  ...  In contrast, the problem associated to the antiferromagnetic RFIM is shown to be an NP-complete optimization problem.  ...  Uhry for pointing to us the connection between the ferromagnetic RFIM and the Min-cutset problem. Fruitful and friendly discussions with Dr. G. Toulouse are gratefully acknowledged.  ... 
doi:10.1051/jphyslet:01985004605017300 fatcat:ds2n5n7kffbyfpeeuznqiavt6i

Quantum Computing for Artificial Intelligence Based Mobile Network Optimization [article]

Furqan Ahmed, Petri Mähönen
2021 arXiv   pre-print
We formulate RSI assignment as quadratic unconstrained binary optimization (QUBO) problem constructed using data ingested from a commercial mobile network, and solve it using a cloud-based commercially  ...  Nevertheless, the proposed framework is highly flexible and holds tremendous potential for harnessing the power of quantum computing in mobile network automation.  ...  Apart from a large number of qubits, a key reason of its relevance to the field of computer science is that it provides a generalized framework to solve combinatorial optimization problems.  ... 
arXiv:2106.13917v1 fatcat:dfg2cuansvcphdhofyu5cmvzim

Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders [article]

Tengfei Ma, Jie Chen, Cao Xiao
2018 arXiv   pre-print
These constraints are not easy to be incorporated into a generative model. In this work, we propose a regularization framework for variational autoencoders as a step toward semantic validity.  ...  There remain, however, substantial challenges for combinatorial structures, including graphs. One of the key challenges lies in the difficulty of ensuring semantic validity in context.  ...  The framework is inspired by the transformation of a constrained optimization problem to a regularized unconstrained one.  ... 
arXiv:1809.02630v2 fatcat:jmwvtcyaznfbrk5dxh2ag5g3my

Towards Stochastic Constraint Programming: A Study of Onine Multi-Choice Knapsack with Deadlines [chapter]

Thierry Benoist, Eric Bourreau, Yves Caseau, Benoît Rottembourg
2001 Lecture Notes in Computer Science  
This benchmark is used to test a framework with four different dynamic strategies that utilize a different combination of the stochastic and combinatorial aspects of the problem.  ...  Most real-life problems are stochastic in nature, which is usually taken into account through different compromises, such as applying a deterministic algorithm to the average values of the input, or performing  ...  Though NP-hard, the afore-mentioned combinatorial optimization problem can be solved with on-the-shelf MIP tools (see [MT90] for a deep description of knapsacklike problems).  ... 
doi:10.1007/3-540-45578-7_5 fatcat:jg4dra4vojedfaideao3uuhx3y

Artificial Intelligence for Computer Games

Abdennour El Rhalibi, Kok Wai Wong, Marc Price
2009 International Journal of Computer Games Technology  
In this paper, the author presents a formal framework for shortest-path decision process problem representation.  ...  They are real-time and very dynamic, encouraging fast and intelligent decisions. Computer games are also often multiagents, making teamwork, competition, and NPC modelling key elements to success.  ...  In this paper, the author presents a formal framework for shortest-path decision process problem representation.  ... 
doi:10.1155/2009/251652 fatcat:itddlsentvbr5eld52mcxt6qsi

First experiences with a parallel architecture testbed in the LHCb trigger system

S Gallorini, D Lucchesi, A Gianelle, S Amerio, M Corvo
2017 Journal of Physics, Conference Series  
This gave us the unique opportunity to test the new hardware and the new algorithms in the real-time environment of the experiment.  ...  During Run2, a node equipped with a GPU has been inserted in the LHCb online monitoring system.  ...  Thanks to Alexey Badalov for developing the Coprocessor Manager and Daniel Campora and Xavier Vilasis Cardona for their help and useful discussions.  ... 
doi:10.1088/1742-6596/898/3/032029 fatcat:ewkwcnwlqnaojcuhs6zfawxrmy

Constrained optimization under uncertainty for decision-making problems: Application to Real-Time Strategy games [article]

Valentin Antuori, Florian Richoux
2019 arXiv   pre-print
Decision-making problems can be modeled as combinatorial optimization problems with Constraint Programming formalisms such as Constrained Optimization Problems.  ...  Here, we propose a way to deal with combinatorial optimization problems under uncertainty within the classical Constrained Optimization Problems formalism by injecting the Rank Dependent Utility from decision  ...  Such environments contain many challenging combinatorial optimization problems. Combinatorial optimization problems can be expressed through different formalisms.  ... 
arXiv:1901.00942v3 fatcat:qklc3ntcbbcqpjbkjc477gy34m
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