Distilling Deep RL Models Into Interpretable Neuro-Fuzzy Systems

Deep Reinforcement Learning uses a deep neural network to encode a policy, which achieves very good performance in a wide range of applications but is widely regarded as a black box model. A more interpretable alternative to deep networks is given by neuro-fuzzy controllers. Unfortunately, neuro-fuzzy controllers often need a large number of rules to solve relatively simple tasks, making them difficult to interpret. In this work, we present an algorithm to distill the policy from a deep Q-network into a compact neuro-fuzzy controller. This allows us to train compact neuro-fuzzy controllers through distillation to solve tasks that they are unable to solve directly, combining the flexibility of deep reinforcement learning and the interpretability of compact rule bases. We demonstrate the algorithm on three well-known environments from OpenAI Gym, where we nearly match the performance of a DQN agent using only 2 to 6 fuzzy rules

The expression, processing and localization of polymorphic membrane proteins in Chlamydia pneumoniae strain CWL029

BACKGROUND: Chlamydiae are obligate intracellular bacteria, which are important human pathogens. Genome sequences of C. trachomatis and C. pneumoniae have revealed the presence of a Chlamydia specific gene family encoding polymorphic outer membrane proteins, Pmps. In C. pneumoniae the family comprises twenty-one members, which are all transcribed. In the present study, the expression, processing and localisation of the sixteen full-length Pmps in C. pneumoniae strain CWL029 have been further investigated by two-dimensional gel electrophoresis and immunofluorescence microscopy. RESULTS: Ten Pmps were identified in elementary bodies (EBs). Eight of these were investigated with respect to time dependent expression and all were found to be up-regulated between 36 and 48 hours post infection. Antibodies against Pmp6, 8, 10, 11 and 21 reacted with chlamydiae when infected cells were formalin fixed. Pmp6, Pmp20 and Pmp21 were found in cleaved forms, and the cleavage sites of Pmp6 and Pmp21 were identified. CONCLUSIONS: The Pmps are heavily up-regulated at the time of conversion of RB to EB, and at least ten Pmps are present in EBs. Due to their reaction in formalin fixation it is likely that Pmp6, 8, 10, 11 and 21 are surface exposed. The identified cleavage sites of Pmp6 and Pmp21 are in agreement with the theory that the Pmps are autotransporters

PDD-SHAP: Fast Approximations for Shapley Values using Functional Decomposition

Because of their strong theoretical properties, Shapley values have become very popular as a way to explain predictions made by black box models. Unfortuately, most existing techniques to compute Shapley values are computationally very expensive. We propose PDD-SHAP, an algorithm that uses an ANOVA-based functional decomposition model to approximate the black-box model being explained. This allows us to calculate Shapley values orders of magnitude faster than existing methods for large datasets, significantly reducing the amortized cost of computing Shapley values when many predictions need to be explained

Evaluating feature attribution methods in the image domain

Feature attribution maps are a popular approach to highlight the most important pixels in an image for a given prediction of a model. Despite a recent growth in popularity and available methods, little attention is given to the objective evaluation of such attribution maps. Building on previous work in this domain, we investigate existing metrics and propose new variants of metrics for the evaluation of attribution maps. We confirm a recent finding that different attribution metrics seem to measure different underlying concepts of attribution maps, and extend this finding to a larger selection of attribution metrics. We also find that metric results on one dataset do not necessarily generalize to other datasets, and methods with desirable theoretical properties such as DeepSHAP do not necessarily outperform computationally cheaper alternatives. Based on these findings, we propose a general benchmarking approach to identify the ideal feature attribution method for a given use case. Implementations of attribution metrics and our experiments are available online

Identification of immune-responsive gene 1 (IRG1) as a target of A20

A20 is a negative regulator of NF-kappa B signaling; it controls inflammatory responses and ensures tissue homeostasis. A20 is thought to restrict NF-kappa B activation both by its ubiquitin-editing activity as well as by its nonenzymatic activities. Besides its role in NF-kappa B signaling, A20 also acts as a protective factor inhibiting apoptosis and necroptosis. Because of the ability of A20 to both ubiquitinate and deubiquitinate substrates, and its involvement in many cellular processes, we hypothesized that deletion of A20 might generally impact on protein levels, thereby disrupting cellular signaling. We performed a differential proteomics study on bone marrow-derived macrophages (BMDMs) from control and myeloid-specific A20 knockout mice, both in untreated conditions and after LPS or TNF treatment, and demonstrated A20-dependent changes in protein expression. Several inflammatory proteins were found up-regulated in the absence of A20, even without an inflammatory stimulus, but, depending on the treatment and the treatment time, more proteins were found regulated. Together these protein changes may affect normal signaling events, which may disturb tissue homeostasis and induce (autoimmune) inflammation, in agreement with A20s proposed identity as a susceptibility gene for inflammatory disease. We further verify that immune-responsive gene 1 (IRG1) is up-regulated in the absence of A20 and that its levels are transcriptionally regulated

Identification of Immune-Responsive Gene 1 (IRG1) as a Target of A20

A20 is a negative regulator of NF-κB signaling; it controls inflammatory responses and ensures tissue homeostasis. A20 is thought to restrict NF-κB activation both by its ubiquitin-editing activity as well as by its nonenzymatic activities. Besides its role in NF-κB signaling, A20 also acts as a protective factor inhibiting apoptosis and necroptosis. Because of the ability of A20 to both ubiquitinate and deubiquitinate substrates, and its involvement in many cellular processes, we hypothesized that deletion of A20 might generally impact on protein levels, thereby disrupting cellular signaling. We performed a differential proteomics study on bone marrow-derived macrophages (BMDMs) from control and myeloid-specific A20 knockout mice, both in untreated conditions and after LPS or TNF treatment, and demonstrated A20-dependent changes in protein expression. Several inflammatory proteins were found up-regulated in the absence of A20, even without an inflammatory stimulus, but, depending on the treatment and the treatment time, more proteins were found regulated. Together these protein changes may affect normal signaling events, which may disturb tissue homeostasis and induce (autoimmune) inflammation, in agreement with A20s proposed identity as a susceptibility gene for inflammatory disease. We further verify that immune-responsive gene 1 (IRG1) is up-regulated in the absence of A20 and that its levels are transcriptionally regulated

Identification of Immune-Responsive Gene 1 (IRG1) as a Target of A20

A20 is a negative regulator of NF-κB signaling; it controls inflammatory responses and ensures tissue homeostasis. A20 is thought to restrict NF-κB activation both by its ubiquitin-editing activity as well as by its nonenzymatic activities. Besides its role in NF-κB signaling, A20 also acts as a protective factor inhibiting apoptosis and necroptosis. Because of the ability of A20 to both ubiquitinate and deubiquitinate substrates, and its involvement in many cellular processes, we hypothesized that deletion of A20 might generally impact on protein levels, thereby disrupting cellular signaling. We performed a differential proteomics study on bone marrow-derived macrophages (BMDMs) from control and myeloid-specific A20 knockout mice, both in untreated conditions and after LPS or TNF treatment, and demonstrated A20-dependent changes in protein expression. Several inflammatory proteins were found up-regulated in the absence of A20, even without an inflammatory stimulus, but, depending on the treatment and the treatment time, more proteins were found regulated. Together these protein changes may affect normal signaling events, which may disturb tissue homeostasis and induce (autoimmune) inflammation, in agreement with A20s proposed identity as a susceptibility gene for inflammatory disease. We further verify that immune-responsive gene 1 (IRG1) is up-regulated in the absence of A20 and that its levels are transcriptionally regulated

Identification of Immune-Responsive Gene 1 (IRG1) as a Target of A20

A20 is a negative regulator of NF-κB signaling; it controls inflammatory responses and ensures tissue homeostasis. A20 is thought to restrict NF-κB activation both by its ubiquitin-editing activity as well as by its nonenzymatic activities. Besides its role in NF-κB signaling, A20 also acts as a protective factor inhibiting apoptosis and necroptosis. Because of the ability of A20 to both ubiquitinate and deubiquitinate substrates, and its involvement in many cellular processes, we hypothesized that deletion of A20 might generally impact on protein levels, thereby disrupting cellular signaling. We performed a differential proteomics study on bone marrow-derived macrophages (BMDMs) from control and myeloid-specific A20 knockout mice, both in untreated conditions and after LPS or TNF treatment, and demonstrated A20-dependent changes in protein expression. Several inflammatory proteins were found up-regulated in the absence of A20, even without an inflammatory stimulus, but, depending on the treatment and the treatment time, more proteins were found regulated. Together these protein changes may affect normal signaling events, which may disturb tissue homeostasis and induce (autoimmune) inflammation, in agreement with A20s proposed identity as a susceptibility gene for inflammatory disease. We further verify that immune-responsive gene 1 (IRG1) is up-regulated in the absence of A20 and that its levels are transcriptionally regulated