808 research outputs found
Planning When Goals Change: A Moving Target Search Approach
International audienceDevising intelligent robots or agents that interact with humans is a major challenge for artificial intelligence. In such contexts, agents must constantly adapt their decisions according to human activities and modify their goals. In this paper, we tackle this problem by introducing a novel planning approach, called Moving Goal Planning (MGP), to adapt plans to goal evolutions. This planning algorithm draws inspiration from Moving Target Search (MTS) algorithms. In order to limit the number of search iterations and to improve its efficiency, MGP delays as much as possible triggering new searches when the goal changes over time. To this purpose, MGP uses two strategies: Open Check (OC) that checks if the new goal is still in the current search tree and Plan Follow (PF) that estimates whether executing actions of the current plan brings MGP closer to the new goal. Moreover, MGP uses a parsimonious strategy to update incrementally the search tree at each new search that reduces the number of calls to the heuristic function and speeds up the search. Finally, we show evaluation results that demonstrate the effectiveness of our approach
Neural progenitor cell implants modulate vascular endothelial growth factor and brain-derived neurotrophic factor expression in rat axotomized neurons
Axotomy of central neurons leads to functional and structural alterations which largely revert when neural progenitor cells (NPCs) are implanted in the lesion site. The new microenvironment created by NPCs in the host tissue might modulate in the damaged neurons the expression of a high variety of molecules with relevant roles in the repair mechanisms, including neurotrophic factors. In the present work, we aimed to analyze changes in neurotrophic factor expression in axotomized neurons induced by NPC implants. For this purpose, we performed immunofluorescence followed by confocal microscopy analysis for the detection of vascular endothelial growth factor (VEGF), brain-derived neurotrophic factor (BDNF), neurotrophin-3 (NT-3) and nerve growth factor (NGF) on brainstem sections from rats with axotomy of abducens internuclear neurons that received NPC implants (implanted group) or vehicle injections (axotomized group) in the lesion site. Control abducens internuclear neurons were strongly immunoreactive to VEGF and BDNF but showed a weak staining for NT-3 and NGF. Comparisons between groups revealed that lesioned neurons from animals that received NPC implants showed a significant increase in VEGF content with respect to animals receiving vehicle injections. However, the immunoreactivity for BDNF, which was increased in the axotomized group as compared to control, was not modified in the implanted group. The modifications induced by NPC implants on VEGF and BDNF content were specific for the population of axotomized abducens internuclear neurons since the neighboring abducens motoneurons were not affected. Similar levels of NT-3 and NGF immunolabeling were obtained in injured neurons from axotomized and implanted animals. Among all the analyzed neurotrophic factors, only VEGF was expressed by the implanted cells in the lesion site. Our results point to a role of NPC implants in the modulation of neurotrophic factor expression by lesioned central neurons, which might contribute to the restorative effects of these implants
Phase Transition in the Number Partitioning Problem
Number partitioning is an NP-complete problem of combinatorial optimization.
A statistical mechanics analysis reveals the existence of a phase transition
that separates the easy from the hard to solve instances and that reflects the
pseudo-polynomiality of number partitioning. The phase diagram and the value of
the typical ground state energy are calculated.Comment: minor changes (references, typos and discussion of results
Random Costs in Combinatorial Optimization
The random cost problem is the problem of finding the minimum in an
exponentially long list of random numbers. By definition, this problem cannot
be solved faster than by exhaustive search. It is shown that a classical
NP-hard optimization problem, number partitioning, is essentially equivalent to
the random cost problem. This explains the bad performance of heuristic
approaches to the number partitioning problem and allows us to calculate the
probability distributions of the optimum and sub-optimum costs.Comment: 4 pages, Revtex, 2 figures (eps), submitted to PR
Optimal combinations of imperfect objects
We address the question of how to make best use of imperfect objects, such as
defective analog and digital components. We show that perfect, or near-perfect,
devices can be constructed by taking combinations of such defects. Any
remaining objects can be recycled efficiently. In addition to its practical
applications, our `defect combination problem' provides a novel generalization
of classical optimization problems.Comment: 4 pages, 3 figures, minor change
Entropy-based analysis of the number partitioning problem
In this paper we apply the multicanonical method of statistical physics on
the number-partitioning problem (NPP). This problem is a basic NP-hard problem
from computer science, and can be formulated as a spin-glass problem. We
compute the spectral degeneracy, which gives us information about the number of
solutions for a given cost and cardinality . We also study an extension
of this problem for partitions. We show that a fundamental difference on
the spectral degeneracy of the generalized () NPP exists, which could
explain why it is so difficult to find good solutions for this case. The
information obtained with the multicanonical method can be very useful on the
construction of new algorithms.Comment: 6 pages, 4 figure
Statins, bone, and neurofibromatosis type 1
Neurofibromatosis type 1 (NF1) is a dominantly inherited multi-system disorder. Major features include pigmentary abnormalities, benign tumors of the nerve sheath (neurofibromas), malignant tumors, learning disabilities, and skeletal dysplasia. The NF1 gene functions as a tumor suppressor, but haploinsuffiency probably accounts for some aspects of the non-tumor phenotype. The protein product, neurofibromin, is a Ras GTPase-activating protein, and various Ras pathway inhibitors are being tested in preclinical models and clinical trials for effectiveness in treating NF1 complications. This month in BMC Medicine, a paper by Kolanczyk et al describes a preclinical mouse model for tibial dysplasia and provides evidence that the drug lovastatin – in use to treat cardiovascular disease – may be beneficial, opening the door to clinical trials in humans
Synthesis and Optimization of Reversible Circuits - A Survey
Reversible logic circuits have been historically motivated by theoretical
research in low-power electronics as well as practical improvement of
bit-manipulation transforms in cryptography and computer graphics. Recently,
reversible circuits have attracted interest as components of quantum
algorithms, as well as in photonic and nano-computing technologies where some
switching devices offer no signal gain. Research in generating reversible logic
distinguishes between circuit synthesis, post-synthesis optimization, and
technology mapping. In this survey, we review algorithmic paradigms ---
search-based, cycle-based, transformation-based, and BDD-based --- as well as
specific algorithms for reversible synthesis, both exact and heuristic. We
conclude the survey by outlining key open challenges in synthesis of reversible
and quantum logic, as well as most common misconceptions.Comment: 34 pages, 15 figures, 2 table
Platform Dependent Verification: On Engineering Verification Tools for 21st Century
The paper overviews recent developments in platform-dependent explicit-state
LTL model checking.Comment: In Proceedings PDMC 2011, arXiv:1111.006
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