855 research outputs found
Identification of unexpected decisions in Partially Observable Monte Carlo Planning: a rule-based approach
Partially Observable Monte-Carlo Planning (POMCP) is a powerful online algorithm able to generate approximate policies for large Partially Observable Markov Decision Processes. The online nature of this method supports scalability by avoiding complete policy representation. The lack of an explicit representation however hinders interpretability. In this work, we propose a methodology based on Satisfiability Modulo Theory (SMT) for analyzing POMCP policies by inspecting their traces, namely sequences of belief-action-observation triplets generated by the algorithm. The proposed method explores local properties of policy behavior to identify unexpected decisions. We propose an iterative process of trace analysis consisting of three main steps, i) the definition of a question by means of a parametric logical formula describing (probabilistic) relationships between beliefs and actions, ii) the generation of an answer by computing the parameters of the logical formula that maximize the number of satisfied clauses (solving a MAX-SMTproblem), iii) the analysis of the generated logical formula and the related decision boundaries for identifying unexpected decisions made by POMCP with respect to the original question. We evaluate our approach on Tiger, a standard benchmark for POMDPs, and a real-world problem related to mobile robot navigation. Results show that the approach can exploit human knowledge on the domain, outperforming state-of-the-art anomaly detection methods in identifying unexpected decisions. An improvement of the Area Under Curve up to 47% has been achieved in our tests
Policy Interpretation for Partially Observable Monte-Carlo Planning: A Rule-Based Approach
Partially Observable Monte-Carlo Planning (POMCP) is a powerful online algorithm that can generate online policies for large Partially Observable Markov Decision Processes. The lack of an explicit representation of the policy, however, hinders interpretability. In this work, we present a MAX-SMT based methodology to iteratively explore local properties of the policy. Our approach generates a compact and informative representation that describes the system under investigation
Explaining the influence of prior knowledge on POMCP policies
Partially Observable Monte Carlo Planning is a recently proposed online planning algorithm which makes use of Monte Carlo Tree Search to solve Partially Observable Monte Carlo Decision Processes. This solver is very successful because of its capability to scale to large uncertain environments, a very important property for current real-world planning problems. In this work we propose three main contributions related to POMCP usage and interpretability. First, we introduce a new planning problem related to mobile robot collision avoidance in paths with uncertain segment difficulties, and we show how POMCP performance in this context can take advantage of prior knowledge about segment difficulty relationships. This problem has direct real-world applications, such as, safety management in industrial environments where human-robot interaction is a crucial issue. Then, we present an experimental analysis about the relationships between prior knowledge provided to the algorithm and performance improvement, showing that in our case study prior knowledge affects two main properties, namely, the distance between the belief and the real state, and the mutual information between segment difficulty and action taken in the segment. This analysis aims to improve POMCP explainability, following the line of recently proposed eXplainable AI and, in particular, eXplainable planning. Finally, we analyze results on a synthetic case study and show how the proposed measures can improve the understanding about internal planning mechanisms
Is accounting enforcement related to risk-taking in the banking industry?
Using a sample of banks from 36 countries, we document that accounting enforcement is negatively related to bank risk-taking. We also provide evidence that accounting enforcement enhances bank stability during the crisis. In addition, we show that banks assume less risk through more conservative lending decisions and a reduction in complexity in jurisdictions with higher accounting enforcement. Our results show that formal institutions such as accounting enforcement are associated with bank financial decisions and risk-taking behavior
Effect of juice turbidity on fermentative volatile compounds in white wines
'Chardonnay' (n = 4), 'Pinot gris' (n = 3) and 'Müller-Thurgau' juices (n = 3), each at 6 turbidity levels (15, 45, 86, 141, 215 and 350 NTU) obtained by adding increasing amounts of their own fine juice lees, were fermented using 'Montrachet Red Star' yeast. The main volatile compounds in free form which may have a sensory role were measured using GC-FID, with a DB-WAX column, after fixing onto Isolute ENV+ resin. Changes for around 40 volatile compounds and fermentation parameters are shown. Juice turbidity levels just below 100 NTU are the best compromise for obtaining adequate fruity notes and minimising languishing fermentation and off-flavours in white wine, if correct microbiology management at the winery is guaranteed, whereas slightly higher NTU levels could contribute to a slightly more complex aroma. However, variability due to juice turbidity in the range investigated is lower than variability due to yeast strain observed in a previous experiment. Thus the choice of yeast strain to direct white wine aroma must be overriding as compared to NTU levels.
Effects of forcing in three dimensional turbulent flows
We present the results of a numerical investigation of three-dimensional
homogeneous and isotropic turbulence, stirred by a random forcing with a power
law spectrum, . Numerical simulations are performed at
different resolutions up to . We show that at varying the spectrum slope
, small-scale turbulent fluctuations change from a {\it forcing independent}
to a {\it forcing dominated} statistics. We argue that the critical value
separating the two behaviours, in three dimensions, is . When the
statistics is forcing dominated, for , we find dimensional scaling, i.e.
intermittency is vanishingly small. On the other hand, for , we find the
same anomalous scaling measured in flows forced only at large scales. We
connect these results with the issue of {\it universality} in turbulent flows.Comment: 4 pages, 4 figure
NUV-HD SiPMs with metal-filled trenches
In this paper we present the performance of a new SiPM that is sensitive to blue light and features narrow metal-filled trenches placed in the area around the single-photon avalanche diodes (SPADs) that allow an almost complete suppression the internal optical crosstalk. In particular, we show the benefits of this technological upgrade in terms of electro-optical SiPM performance when compared to the previous technology which had only a partial optical screening between the SPADs. The most relevant effect is the much higher bias voltage that can be applied to the new device before the noise diverges. This allows to optimize and improve both the photon detection efficiency and the single-photon time resolution. We also coupled the SiPMs to LYSO scintillators to verify the performance for possible application in Positron-Emission Tomography. Thanks to the better electro-optical features we were able to measure an improved coincidence time resolution. Furthermore, the optimal voltage operation region is substantially larger, making this SiPM more suitable for real system application where thousands of channels have to provide stable and reproducible performance
Oral Feeding Competences of Healthy Preterm Infants: A Review
Background. With increasing sophistication and technology, survival rates hugely improved among preterm infants admitted to the neonatal intensive care unit. Nutrition and feeding remain a challenge and preterm infants are at high risk of encountering oral feeding difficulties. Objective. To determine what facts may impact on oral feeding readiness and competence and which kind of interventions should enhance oral feeding performance in preterm infants. Search Strategy. MEDILINE database was explored and articles relevant to this topic were collected starting
from 2009 up to 2011. Main Results. Increasingly robust alertness prior to and during feeding does positively impact the infant's feeding Skills. The review found that oral and non-oral sensorimotor interventions, provided singly or in combination, shortened the transition time to independent oral feeding in preterm infants and that preterm infants who received a combined oral and sensorimotor intervention demonstrated more advanced nutritive sucking, suck-swallow and swallow-respiration coordination than those who received an oral or sensorimotor intervention singly
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