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Anytime Focal Search with Applications

Liron Cohen, Matias Greco, Hang Ma, Carlos Hernandez, Ariel Felner, T. K. Satish Kumar, Sven Koenig
<span title="">2018</span> <i title="International Joint Conferences on Artificial Intelligence Organization"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vfwwmrihanevtjbbkti2kc3nke" style="color: black;">Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence</a> </i> &nbsp;
Focal search (FS) is a bounded-suboptimal search (BSS) variant of A*. Like A*, it uses an open list whose states are sorted in increasing order of their f-values.  ...  On the theoretical side, we show that AFS is bounded suboptimal and that anytime potential search (ATPS/ANA*), a state-of-the-art anytime bounded-cost search (BCS) variant of A*, is a special case of AFS  ...  This makes AFS simpler to understand and implement. Theorem 1.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24963/ijcai.2018/199">doi:10.24963/ijcai.2018/199</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/ijcai/0002G0HFKK18.html">dblp:conf/ijcai/0002G0HFKK18</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/a2iijgtyrbdi7iomsduubef43u">fatcat:a2iijgtyrbdi7iomsduubef43u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190221225330/http://pdfs.semanticscholar.org/3006/a27c83b69990e5dfa4dad42d16acb67e1951.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/30/06/3006a27c83b69990e5dfa4dad42d16acb67e1951.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24963/ijcai.2018/199"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Exploiting Learned Policies in Focal Search [article]

Pablo Araneda, Matias Greco, Jorge A. Baier
<span title="2021-08-03">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The problem of how to effectively use a learned policy within a bounded-suboptimal search algorithm remains largely as an open question.  ...  Recent machine-learning approaches to deterministic search and domain-independent planning employ policy learning to speed up search.  ...  WA* is guaranteed to return w-suboptimal solutions when h is admissible. Focal Search Focal Search (FS) (Pearl and Kim 1982) is a well-known bounded-suboptimal search algorithm.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2104.10535v2">arXiv:2104.10535v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ba2cf4m5dja4tmme7ribqdmytq">fatcat:ba2cf4m5dja4tmme7ribqdmytq</a> </span>
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Potential-based bounded-cost search and Anytime Non-Parametric A⁎

Roni Stern, Ariel Felner, Jur van den Berg, Rami Puzis, Rajat Shah, Ken Goldberg
<span title="">2014</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/weoplee4x5anpi62cco5v4higa" style="color: black;">Artificial Intelligence</a> </i> &nbsp;
PTS is designed to solve bounded-cost search problems, which are problems where the task is to find as fast as possible a solution under a given cost bound.  ...  This paper presents two new search algorithms: Potential Search (PTS) and Anytime Potential Search/Anytime Non-Parametric A * (APTS/ANA * ).  ...  Our implementation of ANA * is freely available in his Search-based Planning Library (SBPL) at: http://www.sbpl.net. A.2.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.artint.2014.05.002">doi:10.1016/j.artint.2014.05.002</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/by2aeh47vvdipcqbyrd3ab2msm">fatcat:by2aeh47vvdipcqbyrd3ab2msm</a> </span>
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CBS-Budget (CBSB): A Complete and Bounded Suboptimal Search for Multi-Agent Path Finding [article]

Jaein Lim, Panagiotis Tsiotras
<span title="2022-05-31">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We prove that CBSB is complete and bounded-suboptimal. In our numerical experiments, CBSB finds a near optimal solution for hundreds of agents within a fraction of a second.  ...  Then, we propose a novel bounded-cost variant of CBS, called CBS-Budget (CBSB) by using a bCOA* search at the low-level search of the CBS and by using a modified focal search at the high-level search of  ...  Focal search, or A * [24] , is a bounded-suboptimal search algorithm that maintains two priority queues: OPEN and FOCAL.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2206.00130v1">arXiv:2206.00130v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5yzpdc4k4bcu5m7q24stu26ary">fatcat:5yzpdc4k4bcu5m7q24stu26ary</a> </span>
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Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search [article]

Shinsaku Sakaue, Taihei Oki
<span title="2022-05-24">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Finally, we discuss a case where the performance of A* is measured by the suboptimality and show that we can sometimes obtain a better guarantee by combining a parameter-dependent worst-case bound with  ...  Greedy best-first search (GBFS) and A* search (A*) are popular algorithms for path-finding on large graphs. Both use so-called heuristic functions, which estimate how close a vertex is to the goal.  ...  A di erence is that while they construct simpler functions with a dynamic programming algorithm, we can use a known worst-case bound on the suboptimality of best-rst search [33] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2205.09963v3">arXiv:2205.09963v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kw2xx4jfozabphfuzjj5vkmqbi">fatcat:kw2xx4jfozabphfuzjj5vkmqbi</a> </span>
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Anytime search in dynamic graphs

Maxim Likhachev, Dave Ferguson, Geoff Gordon, Anthony Stentz, Sebastian Thrun
<span title="">2008</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/weoplee4x5anpi62cco5v4higa" style="color: black;">Artificial Intelligence</a> </i> &nbsp;
In this paper, we present an A * -based anytime search algorithm that produces significantly better solutions than current approaches, while also providing suboptimality bounds on the quality of the solution  ...  One class of planners well-suited to this task are anytime planners, which quickly find an initial, highly suboptimal plan, and then improve this plan until time runs out.  ...  While the path the search returns can be suboptimal, the search also provides a bound on this suboptimality, namely, the by which the heuristic is inflated [25] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.artint.2007.11.009">doi:10.1016/j.artint.2007.11.009</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n6ncype3kjdn5dthp6hfbmka7u">fatcat:n6ncype3kjdn5dthp6hfbmka7u</a> </span>
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Page 8327 of Mathematical Reviews Vol. , Issue 2000k [page]

<span title="">2000</span> <i title="American Mathematical Society"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_mathematical-reviews" style="color: black;">Mathematical Reviews </a> </i> &nbsp;
High computational complexity of optimal solutions suggests employing suboptimal estimation algorithms.  ...  In addition, a guaranteed cost problem, solved by LMI optimization combined with line search, is introduced in order to provide robust performance.” 2000k:93020 93B35 93B51 Mahmoud, Magdi S.  ... 
<span class="external-identifiers"> </span>
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Training-based channel estimation for multiple-antenna broadband transmissions

C. Fragouli, N. Al-Dhahir, W. Turin
<span title="">2003</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ra4txhbrwnbwzk3lwinyjovpbe" style="color: black;">IEEE Transactions on Wireless Communications</a> </i> &nbsp;
Performance bounds derived indicate that these sequences achieve near-optimum performance.  ...  Instead, exhaustive searches can identify suboptimal sequences according to some performance criteria. Tables of such sequences from a BPSK alphabet are provided, for example, in [12] .  ...  Moreover, when optimal sequences do not exist, instead of exhaustive searches we propose a method that identifies suboptimal sequences from a standard signal constellation with a small MSE increase from  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/twc.2003.809454">doi:10.1109/twc.2003.809454</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5pk4hlzzhngqnfudzwgr7jnora">fatcat:5pk4hlzzhngqnfudzwgr7jnora</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190223180554/http://pdfs.semanticscholar.org/4b0b/a29de687063bef36db9204a34e736585e4e8.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4b/0b/4b0ba29de687063bef36db9204a34e736585e4e8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/twc.2003.809454"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Causal-CSIT rate adaptation for block-fading channels

Khoa D. Nguyen, Roy Timo, Lars. K. Rasmussen
<span title="">2015</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ux5tf45dtrgptnezraiii73msm" style="color: black;">2015 IEEE International Symposium on Information Theory (ISIT)</a> </i> &nbsp;
A suboptimal rate adaptation strategy is developed for sequential random codes. Numerical results show that significant performance gains are achievable with the proposed adaptation scheme.  ...  Meanwhile, letting α(c 1 , c 2 ) = 1 in (22) returns the simpler Gallager's upper bound on error probability [13] . Gallager's bound is not tight when the transmission rate is close to capacity.  ...  Recall that the suboptimal causal rate adaptation scheme is solved using the Gallager's bound (setting α(c 1 , c 2 ) = 1 in (22)).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/isit.2015.7282475">doi:10.1109/isit.2015.7282475</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/isit/NguyenTR15.html">dblp:conf/isit/NguyenTR15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3e4um7iqrvdt7m3cqskbtxe7bq">fatcat:3e4um7iqrvdt7m3cqskbtxe7bq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170830001935/http://mediatum.ub.tum.de/doc/1272147/1272147.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/81/33/81334a2ef4fa9e12190ea83cea9517356f13dd21.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/isit.2015.7282475"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

An order optimal policy for exploiting idle spectrum in cognitive radio networks [article]

Jan Oksanen, Visa Koivunen
<span title="2017-09-01">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The proposed recency based approach readily allows constructing the exploration bonus such that it will grow the time interval between consecutive sensing time instants of a suboptimal band exponentially  ...  For example the average time complexity of binary search is , where is the size of the search grid that essentially sets the accuracy of the optimal upper confidence bound.  ...  In [21] , a class of policies based on sample means and upper confidence bounds was proposed. These policies were simpler compared to those in [12] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1709.00237v1">arXiv:1709.00237v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5xhh7mypvzgajcy4aao6pbxpka">fatcat:5xhh7mypvzgajcy4aao6pbxpka</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200822051509/https://arxiv.org/ftp/arxiv/papers/1709/1709.00237.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7f/46/7f468a5d95ef9d5470fb9d8e7acb863f7881c3c1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1709.00237v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Regularization Techniques and Suboptimal Solutions to Optimization Problems in Learning from Data

Giorgio Gnecco, Marcello Sanguineti
<span title="">2010</span> <i title="MIT Press - Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rckx6fqoszfvva5c53bqivu5am" style="color: black;">Neural Computation</a> </i> &nbsp;
Theoretical features of the associated optimization problems are studied, and sparse suboptimal solutions are searched for.  ...  Rates of approximate optimization are estimated for sequences of suboptimal solutions formed by linear combinations of n-tuples of computational units, and statistical learning bounds are derived.  ...  in which one searches for suboptimal solutions) the difference between the expected and the empirical errors.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco.2009.05-08-786">doi:10.1162/neco.2009.05-08-786</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/19922296">pmid:19922296</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vlib3ok4f5alva7upx47qp37xi">fatcat:vlib3ok4f5alva7upx47qp37xi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810164319/http://www.dist.unige.it/ggnecco/NECO1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c0/55/c055ba0ec67ebb213cb210f89f3b0e7aba67818a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco.2009.05-08-786"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> mitpressjournals.org </button> </a>

Ultra-reliable communication over vulnerable all-optical networks via lightpath diversity

Yonggang Wen, V.W.S. Chan
<span title="">2005</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/onirm7ye2bfobnpwuwaopap5yu" style="color: black;">IEEE Journal on Selected Areas in Communications</a> </i> &nbsp;
Closed-form error bounds for both receivers are obtained and compared with the "genie-aided" limit of the lightpath diversity scheme.  ...  It indicates that the simpler EGC receiver is preferred over the complicated optimum receiver in practical receiver design.  ...  a simpler architecture.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jsac.2005.851763">doi:10.1109/jsac.2005.851763</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rasmd55es5dbjiookoohcisbvm">fatcat:rasmd55es5dbjiookoohcisbvm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829014920/http://www.ntu.edu.sg/home/ygwen/Paper/WC-JSAC-05.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/7a/57/7a577e357df04a1153d2e559bb046304f8e5476a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/jsac.2005.851763"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Nearly optimal simple explicit MPC controllers with stability and feasibility guarantees

J. Holaza, B. Takács, M. Kvasnica, S. Di Cairano
<span title="2014-07-28">2014</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qurgrf3jcrdx5fxrge5gukpyxq" style="color: black;">Optimal control applications &amp; methods</a> </i> &nbsp;
In the first step, we devise a simpler polyhedral partition by solving a parametric optimization problem.  ...  In the first step, we devise a simpler polyhedral partition by solving a parametric optimization problem.  ...  The price we are willing to pay for obtaining a simpler representation is suboptimality of Q . / with respect to the optimal representation . /.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1002/oca.2131">doi:10.1002/oca.2131</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/w2a6z7giwzg4batapnds2r4ium">fatcat:w2a6z7giwzg4batapnds2r4ium</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170705104938/http://www.merl.com/publications/docs/TR2014-087.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/57/94/57949b49d75d19fa0f152f066a84e4987763a745.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1002/oca.2131"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> wiley.com </button> </a>

A Sensing Policy Based on Confidence Bounds and a Restless Multi-Armed Bandit Model [article]

Jan Oksanen, Visa Koivunen, H. Vincent Poor
<span title="2012-11-19">2012</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This exponential growth between suboptimal sensing time instances leads to logarithmically growing weak regret.  ...  It is shown that the proposed policy attains asymptotically logarithmic weak regret rate when the rewards are bounded independent and identically distributed or finite state Markovian.  ...  However, the policy in this paper attains a simpler form and according to our simulation also yields better performance when the rewards are bounded.  ... 
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Page 3077 of Mathematical Reviews Vol. , Issue 2003d [page]

<span title="">2003</span> <i title="American Mathematical Society"> <a target="_blank" rel="noopener" href="https://archive.org/details/pub_mathematical-reviews" style="color: black;">Mathematical Reviews </a> </i> &nbsp;
We present closed- form suboptimality bounds (approximate optimality) for Klimov’s rule, which imply that its suboptimality gap is uniformly bounded above with respect to (i) external arrival rates, as  ...  With these constraints the search for stable traffic equilibria in case of given demands becomes equivalent to the search for feasible multicommodity flows.  ... 
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