scholarly journals New Islands of Tractability of Cost-Optimal Planning

2008 ◽  
Vol 32 ◽  
pp. 203-288 ◽  
Author(s):  
M. Katz ◽  
C. Domshlak

We study the complexity of cost-optimal classical planning over propositional state variables and unary-effect actions. We discover novel problem fragments for which such optimization is tractable, and identify certain conditions that differentiate between tractable and intractable problems. These results are based on exploiting both structural and syntactic characteristics of planning problems. Specifically, following Brafman and Domshlak (2003), we relate the complexity of planning and the topology of the causal graph. The main results correspond to tractability of cost-optimal planning for propositional problems with polytree causal graphs that either have O(1)-bounded in-degree, or are induced by actions having at most one prevail condition each. Almost all our tractability results are based on a constructive proof technique that connects between certain tools from planning and tractable constraint optimization, and we believe this technique is of interest on its own due to a clear evidence for its robustness.

2008 ◽  
Vol 31 ◽  
pp. 319-351 ◽  
Author(s):  
O. Gimenez ◽  
A. Jonsson

We present three new complexity results for classes of planning problems with simple causal graphs. First, we describe a polynomial-time algorithm that uses macros to generate plans for the class 3S of planning problems with binary state variables and acyclic causal graphs. This implies that plan generation may be tractable even when a planning problem has an exponentially long minimal solution. We also prove that the problem of plan existence for planning problems with multi-valued variables and chain causal graphs is NP-hard. Finally, we show that plan existence for planning problems with binary state variables and polytree causal graphs is NP-complete.


2009 ◽  
Vol 34 ◽  
pp. 675-706 ◽  
Author(s):  
O. Giménez ◽  
A. Jonsson

Recently, considerable focus has been given to the problem of determining the boundary between tractable and intractable planning problems. In this paper, we study the complexity of planning in the class C_n of planning problems, characterized by unary operators and directed path causal graphs. Although this is one of the simplest forms of causal graphs a planning problem can have, we show that planning is intractable for C_n (unless P = NP), even if the domains of state variables have bounded size. In particular, we show that plan existence for C_n^k is NP-hard for k>=5 by reduction from CNFSAT. Here, k denotes the upper bound on the size of the state variable domains. Our result reduces the complexity gap for the class C_n^k to cases k=3 and k=4 only, since C_n^2 is known to be tractable.


Author(s):  
Christer Bäckström ◽  
Peter Jonsson ◽  
Sebastian Ordyniak

Complexity analysis based on the causal graphs of planning instances is a highly important research area. In particular, tractability results have led to new methods for constructing domain-independent heuristics. Important early examples of such results were presented by, for instance, Brafman & Domshlak and Katz & Keyder. More general results based on polytrees and bounding certain parameters were subsequently derived by Aghighi et al. and Ståhlberg. We continue this line of research by analyzing cost-optimal planning for instances with a polytree causal graph, bounded domain size and bounded depth. We show that no further restrictions are necessary for tractability, thus generalizing the previous results. Our approach is based on a novel method of closely analysing optimal plans: we recursively decompose the causal graph in a way that allows for bounding the number of variable changes as a function of the depth, using a reording argument and a comparison with prefix trees of known size. We then transform the planning instances into tree-structured constraint satisfaction instances.


2015 ◽  
Vol 22 (4) ◽  
pp. 377-382 ◽  
Author(s):  
G. Wang ◽  
X. Chen

Abstract. Almost all climate time series have some degree of nonstationarity due to external driving forces perturbing the observed system. Therefore, these external driving forces should be taken into account when constructing the climate dynamics. This paper presents a new technique of obtaining the driving forces of a time series from the slow feature analysis (SFA) approach, and then introduces them into a predictive model to predict nonstationary time series. The basic theory of the technique is to consider the driving forces as state variables and to incorporate them into the predictive model. Experiments using a modified logistic time series and winter ozone data in Arosa, Switzerland, were conducted to test the model. The results showed improved prediction skills.


2005 ◽  
Vol 120 ◽  
pp. 31-43 ◽  
Author(s):  
Douglas Bridges ◽  
Luminiţa Vîţă

2021 ◽  
Author(s):  
Ruby Barnard-Mayers ◽  
Hiba Kouser ◽  
Jamie A. Cohen ◽  
Katherine Tassiopoulos ◽  
Ellen C. Caniglia ◽  
...  

Background: Developing a causal graph is an important step in etiologic research planning and can be used to highlight data flaws and irreparable bias and confounding. Recent findings have suggested that the human papillomavirus (HPV) vaccine is less effective in protection against HPV associated disease in a population of girls living with HIV. Development: In order to understand the relationship between HIV status and HPV vaccine effectiveness, it is important to outline the key assumptions of the causal mechanisms before designing a study to investigate the effect of the HPV vaccine in girls living with HIV infection. Application: We present a causal graph to describe our assumptions and proposed approach to explore this relationship. We hope to obtain feedback on our assumptions prior to data analysis and exemplify the process for designing an etiologic study.Conclusion: The approach we lay out in this paper may be useful for other researchers who have an interest in using causal graphs to describe and assess assumptions in their own research prior to undergoing data collection and/or analysis.


2013 ◽  
Vol 48 ◽  
pp. 783-812 ◽  
Author(s):  
C. Domshlak ◽  
A. Nazarenko

For almost two decades, monotonic, or ``delete free,'' relaxation has been one of the key auxiliary tools in the practice of domain-independent deterministic planning. In the particular contexts of both satisficing and optimal planning, it underlies most state-of-the-art heuristic functions. While satisficing planning for monotonic tasks is polynomial-time, optimal planning for monotonic tasks is NP-equivalent. Here we establish both negative and positive results on the complexity of some wide fragments of optimal monotonic planning, with the fragments being defined around the causal graph topology. Our results shed some light on the link between the complexity of general optimal planning and the complexity of optimal planning for the respective monotonic relaxations.


Author(s):  
C. Y. Cyrus Chu

The demographic models I reviewed in previous chapters are all one-sex models, in which the sex referred to is usually the female. This setting can be justified if we assume either that the life-cycle vital rates (as functions of state variables) for both sexes are the same or that the population dynamics are determined by one sex alone, independent of the possibly relative abundance of the other sex. However, at least for human population, neither assumption is valid. The ratio of newborn girls and newborn boys is close to one, but is less than one for almost all countries in the world. The age-specific mortality rates of women are also lower than those of men worldwide. This is called sexual dimorphism in the demography literature. Such a dimorphism makes the study of two-sex models indispensable. If we look at the male and female vital rates, we find that the differences are small. Despite this small difference, population dynamics derived solely from male vital rates and those derived solely from female vital rates will show ever-increasing differences with the passage of time. Furthermore, because the intrinsic growth rates derived from male and female lines, respectively, are distinct, we cannot avoid the undesirable conclusion that, if we do not incorporate males and females in a unified model, eventually the sex ratio will become either zero or infinity, which is never the case in reality. This is the inconsistency we have to overcome while dealing with population models with two sexes. Another technical difficulty with two-sex modeling has to do with the irreducibility of the state-transition matrix. I mentioned in chapters 2 and 3 that in an age-specific one-sex model, because people older than a particular age, say β, are not fertile anymore, the age group older than β is an absorbing set; hence, our focus of population dynamics can be restricted to the age set [0, β]. This is why we can transform the n × n Leslie matrix to a Lolka renewal equation. In a two-sex model, however, there does not exist a common upper bound for the reproduction of both sexes, for a male older than β can marry a female younger than β and become fertile again.


2014 ◽  
Vol 610 ◽  
pp. 568-578
Author(s):  
Jing Xian Lu ◽  
Christophe Dousson ◽  
Francine Krief

We propose an autonomic QoS and QoE management architecture based on causal graphs for IPTV services over IP access networks. Our solution achieves a global self-diagnosis process based on local knowledge of each network element using a model­-based diagnosis approach. We illustrate this novel approach in an IMS platform and detail the corresponding causal graph and diagnosis process for IPTV services.


2013 ◽  
Vol 2013 ◽  
pp. 1-9
Author(s):  
Junping Zhou ◽  
Weihua Su ◽  
Zhiqiang Ma ◽  
Minghao Yin

This paper explores the phase transitions of the contingent planning problems. We present CONTINGENT PLAN-EXISTENCE algorithm and CONTINGENT PLAN-NONEXISTENCE algorithm for quickly proving that the contingent planning instances have solutions and have no solutions, respectively. By analyzing the two algorithms, the phase transition area of the contingent planning problems is obtained. If the number of the actions is not greater thanθub, the CONTINGENT PLAN-NONEXISTENCE algorithm can prove that nearly all the contingent planning instances have no solution. If the number of the actions is not lower thanθlb, the CONTINGENT PLAN-EXISTENCE algorithm can prove that nearly all the contingent planning instances have solutions. The results of the experiments show that there exist phase transitions from a region where almost all the contingent planning instances have no solution to a region where almost all the contingent planning instances have solutions.


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