Crossmodal Attentive Skill Learner

This paper presents the Crossmodal Attentive Skill Learner (CASL), integrated with the recently-introduced Asynchronous Advantage Option-Critic (A2OC) architecture [Harb et al., 2017] to enable hierarchical reinforcement learning across multiple sensory inputs. We provide concrete examples where the approach not only improves performance in a single task, but accelerates transfer to new tasks. We demonstrate the attention mechanism anticipates and identifies useful latent features, while filtering irrelevant sensor modalities during execution. We modify the Arcade Learning Environment [Bellemare et al., 2013] to support audio queries, and conduct evaluations of crossmodal learning in the Atari 2600 game Amidar. Finally, building on the recent work of Babaeizadeh et al. [2017], we open-source a fast hybrid CPU-GPU implementation of CASL.Comment: International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2018, NIPS 2017 Deep Reinforcement Learning Symposiu

A blue light receptor that mediates RNA binding and translational regulation

Sensory photoreceptor proteins underpin light-dependent adaptations in nature and enable the optogenetic control of organismal behavior and physiology. We identified the bacterial light-oxygen-voltage (LOV) photoreceptor PAL that sequence-specifically binds short RNA stem loops with around 20 nM affinity in blue light and weaker than 1 µM in darkness. A crystal structure rationalizes the unusual receptor architecture of PAL with C-terminal LOV photosensor and N-terminal effector units. The light-activated PAL–RNA interaction can be harnessed to regulate gene expression at the RNA level as a function of light in both bacteria and mammalian cells. The present results elucidate a new signal-transduction paradigm in LOV receptors and conjoin RNA biology with optogenetic regulation, thereby paving the way toward hitherto inaccessible optoribogenetic modalities

Modeling High-Temperature Superconductivity: Correspondence at Bay?

How does a predecessor theory relate to its successor? According to Heinz Post's General Correspondence Principle, the successor theory has to account for the empirical success of its predecessor. After a critical discussion of this principle, I outline and discuss various kinds of correspondence relations that hold between successive scientific theories. I then look in some detail at a case study from contemporary physics: the various proposals for a theory of high-temperature superconductivity. The aim of this case study is to understand better the prospects and the place of a methodological principle such as the Generalized Correspondence Principle. Generalizing from the case study, I will then argue that some such principle has to be considered, at best, as one tool that might guide scientists in their theorizing. Finally I present a tentative account of why principles such as the Generalized Correspondence Principle work so often and why there is so much continuity in scientific theorizing.Articl

The uncertain brain: a co-ordinate based meta-analysis of the neural signatures supporting uncertainty during different contexts

Uncertainty is often inevitable in everyday life and can be both stressful and exciting. Given its relevance to psychopathology and wellbeing, recent research has begun to address the brain basis of uncertainty. In the current review we examined whether there are discrete and shared neural signatures for different uncertain contexts. From the literature we identified three broad categories of uncertainty currently empirically studied using functional MRI (fMRI): basic threat and reward uncertainty, decision-making under uncertainty, and associative learning under uncertainty. We examined the neural basis of each category by using a coordinate based metaanalysis, where brain activation foci from previously published fMRI experiments were drawn together (1998-2017; 87 studies). The analyses revealed shared and discrete patterns of neural activation for uncertainty, such as the insula and amygdala, depending on the category. Such findings will have relevance for researchers attempting to conceptualise uncertainty, as well as clinical researchers examining the neural basis of uncertainty in relation to psychopathology

A Survey on Wireless Sensor Network Security

Wireless sensor networks (WSNs) have recently attracted a lot of interest in the research community due their wide range of applications. Due to distributed nature of these networks and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. This problem is more critical if the network is deployed for some mission-critical applications such as in a tactical battlefield. Random failure of nodes is also very likely in real-life deployment scenarios. Due to resource constraints in the sensor nodes, traditional security mechanisms with large overhead of computation and communication are infeasible in WSNs. Security in sensor networks is, therefore, a particularly challenging task. This paper discusses the current state of the art in security mechanisms for WSNs. Various types of attacks are discussed and their countermeasures presented. A brief discussion on the future direction of research in WSN security is also included.Comment: 24 pages, 4 figures, 2 table

Hierarchical Collective Agent Network (HCAN) for efficient 3 fusion and management of multiple networked sensors

Agent-based software systems and applications are constructed by integrating diverse sets of components that are intelligent, heterogeneous, distributed, and concurrent. This paper describes a multi-agent system to assure the operation efficiency and reliability in data fusion and management of a set of networked distributive sensors (NDS). We discuss the general concept and architecture of a Hierarchical Collective Agent Network (HCAN) and its functional components for learning and adaptive control of the NDS. Sophistication of a HCAN control environment and an anatomy of the agent modules for enabling intelligent data fusion and management are presented. An exemplar HCAN is configured to support dynamic data fusion and automated sensor management in a simulated distributive and collaborative military sensor network for Global Missile Defense (GMD) application

Security and Privacy Issues in Wireless Mesh Networks: A Survey

This book chapter identifies various security threats in wireless mesh network (WMN). Keeping in mind the critical requirement of security and user privacy in WMNs, this chapter provides a comprehensive overview of various possible attacks on different layers of the communication protocol stack for WMNs and their corresponding defense mechanisms. First, it identifies the security vulnerabilities in the physical, link, network, transport, application layers. Furthermore, various possible attacks on the key management protocols, user authentication and access control protocols, and user privacy preservation protocols are presented. After enumerating various possible attacks, the chapter provides a detailed discussion on various existing security mechanisms and protocols to defend against and wherever possible prevent the possible attacks. Comparative analyses are also presented on the security schemes with regards to the cryptographic schemes used, key management strategies deployed, use of any trusted third party, computation and communication overhead involved etc. The chapter then presents a brief discussion on various trust management approaches for WMNs since trust and reputation-based schemes are increasingly becoming popular for enforcing security in wireless networks. A number of open problems in security and privacy issues for WMNs are subsequently discussed before the chapter is finally concluded.Comment: 62 pages, 12 figures, 6 tables. This chapter is an extension of the author's previous submission in arXiv submission: arXiv:1102.1226. There are some text overlaps with the previous submissio