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In this article we study the theoretical properties of Three-way Decision (TWD) based Machine Learning, from the perspective of Computational Learning Theory, as a first attempt to bridge the gap between Machine Learning theory and Uncertainty Representation theory. Drawing on the mathematical theory of orthopairs, we provide a generalization of the PAC learning framework to the TWD setting, and we use this framework to prove a generalization of the Fundamental Theorem of Statistical Learning. We then show, by means of our main result, a connection between TWD and selective prediction.

This two-volume set LNAI 10313 and LNAI 10314 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2017, held in Olsztyn, Poland, in July 2017. The 74 revised full papers presented together with 16 short papers and 16 invited talks, were carefully reviewed and selected from 130 submissions. The papers in this two set-volume of IJCRS 2017 follow the track already rutted by RSCTC and JRS conferences which aimed at unification of many facets of rough set theory from theoretical aspects of the rough set idea bordering on theory of concepts and going through algebraic structures, topological structures, logics for uncertain reasoning, decision algorithms, relations to other theories of vagueness and ambiguity, then to extensions of the rough set idea like granular structures, rough mereology, and to applications of the idea in diverse fields of applied science including hybrid methods like rough-fuzzy, neuro-rough, neuro-rough-fuzzy computing. IJCRS 2017 encompasses topics spread among four main tracks: Rough Sets and Data Science (in relation to RSCTC series organized since 1998); Rough Sets and Granular Computing (in relation to RSFDGrC series organized since 1999); Rough Sets and Knowledge Technology (in relation to RSKT series organized since 2006); and Rough Sets and Intelligent Systems (in relation to RSEISP series organized since 2007).

2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 11-14 August 2014, Item does not contain fulltext

2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, 11-14 August 2014, Item does not contain fulltext, This paper compares population-based and agent-based simulation of the dynamics of group Situation Awareness. The question how Situation Awareness spreads among a team of agents is important for numerous applications. In this paper, a population-based and an agent-based model of this process are proposed, and applied to a case study in aviation. A number of relevant simulations of the models are performed, to investigate whether the behaviour of the population-based model can approximate the pattern produced by the agent-based model. It was demonstrated that, especially for larger populations, the dynamics of the agent-based simulations can be approximated by population-based simulations, since both models demonstrate a similar pattern.

The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100-500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a "router" network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates. © 2010 Zylberberg et al.

The conflict between malware authors and analysts is heating up as both are coming up with new armaments in their armory. Malware authors are employing novel sophisticated techniques like metamorphosis to thwart detection mechanisms while security professionals are budding new ways to confront them. In this paper we formally treat diverse mechanisms of making malware undetectable in general and code mutation techniques in particular. We also supported our argument where possible, through different tools and have revealed their outcome. In the end we give our methodology to make any virus undetectable using amalgamation of hex editing and metamorphic techniques.

RIVM rapport:Abstract niet beschikbaar, The following is an extended summary of the project "A model system approach to biological climate forcing: the example of Emiliania huxleyi," that was carried out within the framework of the Dutch National Programme on Air Pollution and Climate Change (NRP) - phase II. In this report the progress is described that has been made in the formulation of the Dynamic Energy Budget (DEB) Theory that now includes photosynthesis, nutrient limitation and calcification. On top of this the next level of organisation was explored in the adaptation of the model towards a small ecosystem comprising an autotrophic and a heterotrophic organism together with a decomposer, -the dynamics of biomass in vertical profiles has been analysed. At the same time experiments were conducted with E. huxleyi in order to be able to validate the DEB-models at the organismic level. The experiments involved exploration of the genes that control calcification, photosynthesis and nutrition, a detailed description of growth based on chemostat experiments, and an inventory of environmental factors that determine the production of dimethylsulfoniopropionate, the precursor of the biogenic gas dimethylsufide (DMS) that regulates climate once it has reached the atmosphere acting as a source of cloud condensation nuclei.