text stringlengths 27 153 | label stringlengths 27 153 | id int64 0 40k |
|---|---|---|
We present model a mathematical transfer-of-control of strategies. | We present a mathematical model of transfer-of-control strategies. | 3,100 |
on order based loosely causal UCPOP. planner (POCL) VHPOP a is partial link | VHPOP is a partial order causal link (POCL) planner loosely based on UCPOP. | 3,101 |
durative with VHPOP supports actions for temporal incorporating also techniques reasoning. constraint standard by planning | VHPOP also supports planning with durative actions by incorporating standard techniques for temporal constraint reasoning. | 3,102 |
this the extend to paper approach with we temporal In information. deal | In this paper we extend the approach to deal with temporal information. | 3,103 |
discovery. paper presents an approach subgroup expert-guided This to | This paper presents an approach to expert-guided subgroup discovery. | 3,104 |
for the describe We a specifying of system actions. effects | We describe a system for specifying the effects of actions. | 3,105 |
a deviations in model performance. present for expressive timing We generative probabilistic music | We present a probabilistic generative model for timing deviations in expressive music performance. | 3,106 |
model. a of to proposed The is switching state structure equivalent space the model | The structure of the proposed model is equivalent to a switching state space model. | 3,107 |
variables in a musical locations correspond The as switch to score. discrete note | The switch variables correspond to discrete note locations as in a musical score. | 3,108 |
variables continuous denote the The tempo. hidden | The continuous hidden variables denote the tempo. | 3,109 |
results Our with suggest results methods. simulation better sequential | Our simulation results suggest better results with sequential methods. | 3,110 |
capable planning. designed be It the temporal nature to multi-objective handling of of is metric | It is designed to be capable of handling the multi-objective nature of metric temporal planning. | 3,111 |
(i.e., minimum over all plans). cheapest plans | minimum over all plans (i.e., cheapest plans). | 3,112 |
on results we selected problems. report Furthermore, experimental | Furthermore, we report experimental results on selected problems. | 3,113 |
distribution data class twenty-six and, study for learning. determine for the best sets We each, | We study twenty-six data sets and, for each, determine the best class distribution for learning. | 3,114 |
induce domains unary domain's called causal operator the natural However, a structure, graph. | However, unary operator domains induce a natural structure, called the domain's causal graph. | 3,115 |
This and graph effect between preconditions relates each of domain operator. the | This graph relates between the preconditions and effect of each domain operator. | 3,116 |
with our to complexity serializable of results Finally we the of question relate planning subgoals. | Finally we relate our results to the question of complexity of planning with serializable subgoals. | 3,117 |
for empirically, analyze, scheduling behavior theoretically algorithm of types. our and various distribution We the | We analyze, theoretically and empirically, the behavior of our scheduling algorithm for various distribution types. | 3,118 |
to Latin Square our Finally, empirical applying problem. scheduling results algorithm we of present the | Finally, we present empirical results of applying our scheduling algorithm to the Latin Square problem. | 3,119 |
payoff. stochastic common-interest all games receive players identical In an | In common-interest stochastic games all players receive an identical payoff. | 3,120 |
framework populations introduced. the for structured group in is A evolution of modeling mathematical | A framework for the mathematical modeling of evolution in group structured populations is introduced. | 3,121 |
of is fixed The a number large divided groups fixed of into size. population | The population is divided into a fixed large number of groups of fixed size. | 3,122 |
the gene. a viability of leads for a to Hamilton's generalization This condition mutant of | This leads to a generalization of Hamilton's condition for the viability of a mutant gene. | 3,123 |
structural present information positive We an data efficient alone. from that algorithm about examples learns | We present an efficient algorithm that learns structural information about data from positive examples alone. | 3,124 |
on ten Web the We validated algorithm reinduction sources. | We validated the reinduction algorithm on ten Web sources. | 3,125 |
number show of these rules have that desirable a properties. We computational | We show that these rules have a number of desirable computational properties. | 3,126 |
propose number We two rules. manipulating of for also approximation these methods a | We also propose a number of approximation methods for manipulating these two rules. | 3,127 |
manipulate both Experiments in rules to difficult often demonstrate that practice. are | Experiments demonstrate that both rules are often difficult to manipulate in practice. | 3,128 |
study. further style These deserve suggest voting elimination results that rules | These results suggest that elimination style voting rules deserve further study. | 3,129 |
competitors, so, state-of-the-art reveal Our often that experiments outperforms for problems. approach significantly our large | Our experiments reveal that our approach outperforms state-of-the-art competitors, often significantly so, for large problems. | 3,130 |
set. using data test procedure gene a the we expression well-known Finally | Finally we test the procedure using a well-known gene expression data set. | 3,131 |
decomposition systems in a task organize to knowledge. method many used is agent agent Hierarchical | Hierarchical task decomposition is a method used in many agent systems to organize agent knowledge. | 3,132 |
the a team COM-MTDP coordination the novel provides for algorithms. Furthermore, model development basis of | Furthermore, the COM-MTDP model provides a basis for the development of novel team coordination algorithms. | 3,133 |
is for technique a planning. major Search | Search is a major technique for planning. | 3,134 |
of prohibitively the large search space sizes make expensive. search However, | However, prohibitively large sizes of the search space make search expensive. | 3,135 |
efficiency. better main Developing been the functions heuristic has search improving technique for | Developing better heuristic functions has been the main technique for improving search efficiency. | 3,136 |
searches. has POR speeding promise up in shown | POR has shown promise in speeding up searches. | 3,137 |
for In we theory a develop this POR planning. paper, in | In this paper, we develop a theory for POR in planning. | 3,138 |
planning explained new algorithms by previous be We in POR the show can that theory. | We show that previous POR algorithms in planning can be explained by the new theory. | 3,139 |
Based we stronger propose POR a algorithm. on new, the theory, new | Based on the new theory, we propose a new, stronger POR algorithm. | 3,140 |
domains search reduction using Experimental cost on further results algorithm. various the show new planning | Experimental results on various planning domains show further search cost reduction using the new algorithm. | 3,141 |
functions energy solved. can be for quadratic analytically dynamics Hamiltonian | Hamiltonian dynamics for quadratic energy functions can be analytically solved. | 3,142 |
online. are paper this Supplemental materials for available | Supplemental materials for this paper are available online. | 3,143 |
measure approach a is automatic based fuzziness An on histogram threshold presented. | An automatic histogram threshold approach based on a fuzziness measure is presented. | 3,144 |
(SMC) Sequential Carlo become in Monte have horses ABC. work approaches | Sequential Monte Carlo (SMC) approaches have become work horses in ABC. | 3,145 |
of if scientific evaluation likelihood any impossible. For the problematic nearly not challenging problem is | For nearly any challenging scientific problem evaluation of the likelihood is problematic if not impossible. | 3,146 |
for sets statistics are selection Such parameter estimation problems. and model both of constructed sufficient | Such sufficient sets of statistics are constructed for both parameter estimation and model selection problems. | 3,147 |
illustrative apply and to a model our range of We approach selection problems. real-world | We apply our approach to a range of illustrative and real-world model selection problems. | 3,148 |
into to lungs. fit iteratively vessels track the to cylinders them are Model the | Model cylinders are iteratively fit to the vessels to track them into the lungs. | 3,149 |
novel is (SS) metric. surface evaluation accomplished our sparse using Validation | Validation is accomplished using our novel sparse surface (SS) evaluation metric. | 3,150 |
undergone reality improvement Augmented past have years. in considerable | Augmented reality have undergone considerable improvement in past years. | 3,151 |
spread reality augmented enabled of This mass applications. | This enabled mass spread of augmented reality applications. | 3,152 |
constraint been Set represented variables subset in using have multiset bounds. programming typically and | Set and multiset variables in constraint programming have typically been represented using subset bounds. | 3,153 |
offer pruning that runtime. significantly they and demonstrate Results better | Results demonstrate that they offer significantly better pruning and runtime. | 3,154 |
for Repeated interaction individuals dilemma main in the is between maintaining cooperation situations. social mechanism | Repeated interaction between individuals is the main mechanism for maintaining cooperation in social dilemma situations. | 3,155 |
predict that evolutionary We numerically also simulations. show adaptive outcome of the dynamics appositely estimated | We also show that numerically estimated adaptive dynamics appositely predict the outcome of evolutionary simulations. | 3,156 |
achieved through measure is paradigm. stack a new filtering This | This new measure is achieved through a stack filtering paradigm. | 3,157 |
anisotropic variation entropy used this to is the measure. entropy of define directional an Then | Then the entropy variation of this directional entropy is used to define an anisotropic measure. | 3,158 |
been evaluated with real-world method and images. has degraded The artificial | The method has been evaluated with artificial and real-world degraded images. | 3,159 |
its and Kolmogorov-Smirnov test two-sample with biasedness. deals This paper | This paper deals with two-sample Kolmogorov-Smirnov test and its biasedness. | 3,160 |
This in different sizes. case in unbiased of is test general not sample | This test is not unbiased in general in case of different sample sizes. | 3,161 |
values $\alpha$. level of some distribution significance biased out for found We most | We found out most biased distribution for some values of significance level $\alpha$. | 3,162 |
of Here, inconsistency the arises show maps. from that the connectivity the incompleteness we | Here, we show that the inconsistency arises from the incompleteness of the connectivity maps. | 3,163 |
measurements. in transient by Similarly, inputs thalamic the patterns vivo activation recent evoked reproduce | Similarly, the activation patterns evoked by transient thalamic inputs reproduce recent in vivo measurements. | 3,164 |
Markov refer our We Carlo Monte (TMCMC). to Transformation-based new methodology as chain | We refer to our new methodology as Transformation-based Markov chain Monte Carlo (TMCMC). | 3,165 |
properties. our convergence theoretically, establishing the proposal We validate | We validate our proposal theoretically, establishing the convergence properties. | 3,166 |
the savings Remarkable results. acceptance good computational rates are well properties convergence as as and | Remarkable computational savings as well as good convergence properties and acceptance rates are the results. | 3,167 |
performance MIPS shown competitions. two last has international distinguished planning the in | MIPS has shown distinguished performance in the last two international planning competitions. | 3,168 |
longer but Plans schedules. were actions of time-stamped sequences no | Plans were no longer sequences of actions but time-stamped schedules. | 3,169 |
detail. in is latter aspect analyzed The | The latter aspect is analyzed in detail. | 3,170 |
user making. preferences Information automated role in plays key about a decision | Information about user preferences plays a key role in automated decision making. | 3,171 |
representation circumstances. often many quite arguably a natural Such compact in and is | Such a representation is often compact and arguably quite natural in many circumstances. | 3,172 |
In the variables. for many there choice decision is cases, considerable | In many cases, there is considerable choice for the decision variables. | 3,173 |
can such between viewpoint. primal choose a a problems, In we and dual | In such problems, we can choose between a primal and a dual viewpoint. | 3,174 |
comparing models. methodology They constraint a for illustrate also general different | They also illustrate a general methodology for comparing different constraint models. | 3,175 |
complex are understand, reimplement, quite these modify). or However, all systems (to | However, all these systems are quite complex (to understand, reimplement, or modify). | 3,176 |
algorithm introduce solving problem. for Physical-A* this We the (PHA*) | We introduce the Physical-A* algorithm (PHA*) for solving this problem. | 3,177 |
we an Specifically, experimental provide such implementation system. a for | Specifically, we provide an experimental implementation for such a system. | 3,178 |
recovers lost a the A surplus. significant of decommitment fraction phase subsequent | A subsequent decommitment phase recovers a significant fraction of the lost surplus. | 3,179 |
precise determined. between has the yet and relation not been transduction Moreover, induction | Moreover, the precise relation between induction and transduction has not yet been determined. | 3,180 |
implicitly While bound tight, routine. given is computational a this via | While tight, this bound is given implicitly via a computational routine. | 3,181 |
dynamics are simulation according to making and results. management These decision supported models with specified | These dynamics are specified according to management decision making models and supported with simulation results. | 3,182 |
determines Value" of "Fitness article This by results and simulation Optimality". of means "Probability | This article determines simulation results by means of "Fitness Value" and "Probability of Optimality". | 3,183 |
paper, In argue i.e. that this complexification, we | In this paper, we argue that complexification, i.e. | 3,184 |
new goals. these through elaboration both of achieves structure, adding solutions the incremental | the incremental elaboration of solutions through adding new structure, achieves both these goals. | 3,185 |
This technique presents new on a classifier combination theory the Dempster-Shafer based evidence. of paper | This paper presents a new classifier combination technique based on the Dempster-Shafer theory of evidence. | 3,186 |
calculate Captured then are processed speed. vehicle images to | Captured images are then processed to calculate vehicle speed. | 3,187 |
for admissible functions computing for evaluation method problems. a search explore heuristic We | We explore a method for computing admissible heuristic evaluation functions for search problems. | 3,188 |
the as and we domains other extend method Here to that it show applies well. | Here we extend the method and show that it applies to other domains as well. | 3,189 |
We which call partitioned also pattern databases. dynamically for present we heuristics another method additive | We also present another method for additive heuristics which we call dynamically partitioned pattern databases. | 3,190 |
problem disjoint into of for dynamically. partition we the search Here state the each subproblems | Here we partition the problem into disjoint subproblems for each state of the search dynamically. | 3,191 |
presents model repositories. aimed at novel paper This approach a modelling building compositional | This paper presents a novel compositional modelling approach aimed at building model repositories. | 3,192 |
in field It furthers the two respects. | It furthers the field in two respects. | 3,193 |
preferences process. the user Secondly, selection the of model incorporation enables into it | Secondly, it enables the incorporation of user preferences into the model selection process. | 3,194 |
of only plan then We low-dimensional the in belief terms features. | We then plan only in terms of the low-dimensional belief features. | 3,195 |
been measures it Furthermore, also accuracy. that achieve has better reported constrained such can | Furthermore, it has been reported that such constrained measures can also achieve better accuracy. | 3,196 |
result, behavior. to correct it harder is a their guarantee As | As a result, it is harder to guarantee their correct behavior. | 3,197 |
finite-state methods verification for most of the One is of checking. model successful automated systems | One of the most successful methods for automated verification of finite-state systems is model checking. | 3,198 |
the is, The better performance the gets compact one verifier. more the from BDD | The more compact the BDD is, the better performance one gets from the verifier. | 3,199 |
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