28,854 research outputs found
Distributed Adaptive Networks: A Graphical Evolutionary Game-Theoretic View
Distributed adaptive filtering has been considered as an effective approach
for data processing and estimation over distributed networks. Most existing
distributed adaptive filtering algorithms focus on designing different
information diffusion rules, regardless of the nature evolutionary
characteristic of a distributed network. In this paper, we study the adaptive
network from the game theoretic perspective and formulate the distributed
adaptive filtering problem as a graphical evolutionary game. With the proposed
formulation, the nodes in the network are regarded as players and the local
combiner of estimation information from different neighbors is regarded as
different strategies selection. We show that this graphical evolutionary game
framework is very general and can unify the existing adaptive network
algorithms. Based on this framework, as examples, we further propose two
error-aware adaptive filtering algorithms. Moreover, we use graphical
evolutionary game theory to analyze the information diffusion process over the
adaptive networks and evolutionarily stable strategy of the system. Finally,
simulation results are shown to verify the effectiveness of our analysis and
proposed methods.Comment: Accepted by IEEE Transactions on Signal Processin
Grounding semantics in robots for Visual Question Answering
In this thesis I describe an operational implementation of an object detection and description system that incorporates in an end-to-end Visual Question Answering system and evaluated it on two visual question answering datasets for compositional language and elementary visual reasoning
Parameters identification of unknown delayed genetic regulatory networks by a switching particle swarm optimization algorithm
The official published version can be found at the link below.This paper presents a novel particle swarm optimization (PSO) algorithm based on Markov chains and competitive penalized method. Such an algorithm is developed to solve global optimization problems with applications in identifying unknown parameters of a class of genetic regulatory networks (GRNs). By using an evolutionary factor, a new switching PSO (SPSO) algorithm is first proposed and analyzed, where the velocity updating equation jumps from one mode to another according to a Markov chain, and acceleration coefficients are dependent on mode switching. Furthermore, a leader competitive penalized multi-learning approach (LCPMLA) is introduced to improve the global search ability and refine the convergent solutions. The LCPMLA can automatically choose search strategy using a learning and penalizing mechanism. The presented SPSO algorithm is compared with some well-known PSO algorithms in the experiments. It is shown that the SPSO algorithm has faster local convergence speed, higher accuracy and algorithm reliability, resulting in better balance between the global and local searching of the algorithm, and thus generating good performance. Finally, we utilize the presented SPSO algorithm to identify not only the unknown parameters but also the coupling topology and time-delay of a class of GRNs.This research was partially supported by the National Natural Science Foundation of PR China (Grant No. 60874113), the Research Fund for the Doctoral Program of Higher Education (Grant No. 200802550007), the Key Creative Project of Shanghai Education Community (Grant No. 09ZZ66), the Key Foundation Project of Shanghai (Grant No. 09JC1400700), the Engineering and Physical Sciences Research Council EPSRC of the UK under Grant No. GR/S27658/01, the International Science and Technology Cooperation Project of China under Grant No. 2009DFA32050, an International Joint Project sponsored by the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Sex differences in intimate relationships
Social networks have turned out to be of fundamental importance both for our
understanding human sociality and for the design of digital communication
technology. However, social networks are themselves based on dyadic
relationships and we have little understanding of the dynamics of close
relationships and how these change over time. Evolutionary theory suggests
that, even in monogamous mating systems, the pattern of investment in close
relationships should vary across the lifespan when post-weaning investment
plays an important role in maximising fitness. Mobile phone data sets provide
us with a unique window into the structure of relationships and the way these
change across the lifespan. We here use data from a large national mobile phone
dataset to demonstrate striking sex differences in the pattern in the
gender-bias of preferred relationships that reflect the way the reproductive
investment strategies of the two sexes change across the lifespan: these
differences mainly reflect women's shifting patterns of investment in
reproduction and parental care. These results suggest that human social
strategies may have more complex dynamics than we have tended to assume and a
life-history perspective may be crucial for understanding them.Comment: 5 pages, 3 figures, contains electronic supplementary materia
Transferring a Question-Based Dialog Framework to a Distributed Architecture
Inquiry skills are an essential tool for assessing and integrating knowledge. In facilitated face-to-face settings, inquiry skills were improved successfully by using a “question-based dialog” and its resulting visual representation. However, groups that work without a facilitator, or in which members collaborate asynchronously or in different geographical regions, such as Communities of Practice (CoP), cannot schedule face-to-face inquiry meetings. This paper summarises the unmet requirements of CoPs for a collaborative inquiry tool found by previous research on the Noracle model and proposes a distributed Web architecture as a solution. It mitigates the need for a common infrastructure, central coordination or facilitation, addresses the evolutionary nature of communities of practice and reduces the cognitive load for the individual by filtering and organising the representational artefacts with respect to the social network of the community. The implementation we envision in this paper aims at applying the concept to a much broader audience, ultimately replacing the need for local meetings
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