151 research outputs found
Nonapproximability Results for Partially Observable Markov Decision Processes
We show that for several variations of partially observable Markov decision
processes, polynomial-time algorithms for finding control policies are unlikely
to or simply don't have guarantees of finding policies within a constant factor
or a constant summand of optimal. Here "unlikely" means "unless some complexity
classes collapse," where the collapses considered are P=NP, P=PSPACE, or P=EXP.
Until or unless these collapses are shown to hold, any control-policy designer
must choose between such performance guarantees and efficient computation
Role of goblet cell protein CLCA1 in murine DSS colitis
Background The secreted goblet cell protein CLCA1 (chloride channel regulator,
calcium-activated-1) is, in addition to its established role in epithelial
chloride conductance regulation, thought to act as a multifunctional signaling
protein, including cellular differentiation pathways and induction of mucus
production. Specifically, CLCA1 has recently been shown to modulate early
immune responses by regulation of cytokines. Here, we analyze the role of
CLCA1, which is highly expressed and secreted by colon goblet cells, in the
course of murine dextran sodium sulfate-induced colitis. Findings We compared
Clca1-deficient and wild type mice under unchallenged and DSS-challenged
conditions at various time points, including weight loss, colon weight-length-
ratio and histological characterization of inflammation and regeneration.
Expression levels of relevant cytokines, trefoil factor 3 and E-cadherin were
assessed via quantitative PCR and cytometric bead arrays. Lack of CLCA1 was
associated with a more than two-fold increased expression of Cxcl-1- and
Il-17-mRNA during DSS colitis. However, no differences were found between
Clca1-deficient and wild type mice under unchallenged or DSS-challenged
conditions in terms of clinical findings, disease progression, colitis
outcome, epithelial defects or regeneration. Conclusions CLCA1 is involved in
the modulation of cytokine responses in the colon, albeit differently than
what had been observed in the lungs. Obviously, the pathways involved depend
on the type of challenge, time point or tissue environment
False-Name Manipulation in Weighted Voting Games is Hard for Probabilistic Polynomial Time
False-name manipulation refers to the question of whether a player in a
weighted voting game can increase her power by splitting into several players
and distributing her weight among these false identities. Analogously to this
splitting problem, the beneficial merging problem asks whether a coalition of
players can increase their power in a weighted voting game by merging their
weights. Aziz et al. [ABEP11] analyze the problem of whether merging or
splitting players in weighted voting games is beneficial in terms of the
Shapley-Shubik and the normalized Banzhaf index, and so do Rey and Rothe [RR10]
for the probabilistic Banzhaf index. All these results provide merely
NP-hardness lower bounds for these problems, leaving the question about their
exact complexity open. For the Shapley--Shubik and the probabilistic Banzhaf
index, we raise these lower bounds to hardness for PP, "probabilistic
polynomial time", and provide matching upper bounds for beneficial merging and,
whenever the number of false identities is fixed, also for beneficial
splitting, thus resolving previous conjectures in the affirmative. It follows
from our results that beneficial merging and splitting for these two power
indices cannot be solved in NP, unless the polynomial hierarchy collapses,
which is considered highly unlikely
Model Checking CTL is Almost Always Inherently Sequential
The model checking problem for CTL is known to be P-complete (Clarke,
Emerson, and Sistla (1986), see Schnoebelen (2002)). We consider fragments of
CTL obtained by restricting the use of temporal modalities or the use of
negations---restrictions already studied for LTL by Sistla and Clarke (1985)
and Markey (2004). For all these fragments, except for the trivial case without
any temporal operator, we systematically prove model checking to be either
inherently sequential (P-complete) or very efficiently parallelizable
(LOGCFL-complete). For most fragments, however, model checking for CTL is
already P-complete. Hence our results indicate that, in cases where the
combined complexity is of relevance, approaching CTL model checking by
parallelism cannot be expected to result in any significant speedup. We also
completely determine the complexity of the model checking problem for all
fragments of the extensions ECTL, CTL+, and ECTL+
Improving exploration in policy gradient search: Application to symbolic optimization
Many machine learning strategies designed to automate mathematical tasks
leverage neural networks to search large combinatorial spaces of mathematical
symbols. In contrast to traditional evolutionary approaches, using a neural
network at the core of the search allows learning higher-level symbolic
patterns, providing an informed direction to guide the search. When no labeled
data is available, such networks can still be trained using reinforcement
learning. However, we demonstrate that this approach can suffer from an early
commitment phenomenon and from initialization bias, both of which limit
exploration. We present two exploration methods to tackle these issues,
building upon ideas of entropy regularization and distribution initialization.
We show that these techniques can improve the performance, increase sample
efficiency, and lower the complexity of solutions for the task of symbolic
regression.Comment: Published in 1st Mathematical Reasoning in General Artificial
Intelligence Workshop, ICLR 202
The Goblet Cell Protein Clca1 (Alias mClca3 or Gob-5) Is Not Required for Intestinal Mucus Synthesis, Structure and Barrier Function in Naive or DSS- Challenged Mice
The secreted, goblet cell-derived protein Clca1 (chloride channel regulator,
calcium-activated-1) has been linked to diseases with mucus overproduction,
including asthma and cystic fibrosis. In the intestine Clca1 is found in the
mucus with an abundance and expression pattern similar to Muc2, the major
structural mucus component. We hypothesized that Clca1 is required for the
synthesis, structure or barrier function of intestinal mucus and therefore
compared wild type and Clca1-deficient mice under naive and at various time
points of DSS (dextran sodium sulfate)-challenged conditions. The mucus
phenotype in Clca1-deficient compared to wild type mice was systematically
characterized by assessment of the mucus protein composition using proteomics,
immunofluorescence and expression analysis of selected mucin genes on mRNA
level. Mucus barrier integrity was assessed in-vivo by analysis of bacterial
penetration into the mucus and translocation into sentinel organs combined
analysis of the fecal microbiota and ex-vivo by assessment of mucus
penetrability using beads. All of these assays revealed no relevant
differences between wild type and Clca1-deficient mice under steady state or
DSS-challenged conditions in mouse colon. Clca1 is not required for mucus
synthesis, structure and barrier function in the murine colon
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