A Multi-Dimensional Trust Model for Heterogeneous Contract Observations

In this paper we develop a novel probabilistic model of computational trust that allows agents to exchange and combine reputation reports over heterogeneous, correlated multi-dimensional contracts. We consider the specific case of an agent attempting to procure a bundle of services that are subject to correlated quality of service failures (e.g. due to use of shared resources or infrastructure), and where the direct experience of other agents within the system consists of contracts over different combinations of these services. To this end, we present a formalism based on the Kalman filter that represents trust as a vector estimate of the probability that each service will be successfully delivered, and a covariance matrix that describes the uncertainty and correlations between these probabilities. We describe how the agents’ direct experiences of contract outcomes can be represented and combined within this formalism, and we empirically demonstrate that our formalism provides significantly better trustworthiness estimates than the alternative of using separate single-dimensional trust models for each separate service (where information regarding the correlations between each estimate is lost)

Applications of artificial intelligence to mission planning

The scheduling problem facing NASA-Marshall mission planning is extremely difficult for several reasons. The most critical factor is the computational complexity involved in developing a schedule. The size of the search space is large along some dimensions and infinite along others. It is because of this and other difficulties that many of the conventional operation research techniques are not feasible or inadequate to solve the problems by themselves. Therefore, the purpose is to examine various artificial intelligence (AI) techniques to assist conventional techniques or to replace them. The specific tasks performed were as follows: (1) to identify mission planning applications for object oriented and rule based programming; (2) to investigate interfacing AI dedicated hardware (Lisp machines) to VAX hardware; (3) to demonstrate how Lisp may be called from within FORTRAN programs; (4) to investigate and report on programming techniques used in some commercial AI shells, such as Knowledge Engineering Environment (KEE); and (5) to study and report on algorithmic methods to reduce complexity as related to AI techniques

Pleistocene population X-plosion?

Journal ArticleIn two recent papers, Kaessmann et al. presented DNA sequence data from the X chromosome (Xq13.3) of 30 chimpanzees and 69 humans (Kaessmann et al. 1999a; Kaessmann et al. 1999b). These data bear on two longstanding questions involving late Pleistocene demographic history: (1) whether the long-term demography of humans is characterized by explosive population growth, and (2) whether chimps show population growth coinciding temporally with growth in humans

Towards Real-Time Information Processing of Sensor Network Data using Computationally Efficient Multi-output Gaussian Processes

In this paper, we describe a novel, computationally efficient algorithm that facilitates the autonomous acquisition of readings from sensor networks (deciding when and which sensor to acquire readings from at any time), and which can, with minimal domain knowledge, perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental variables will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and to this end, we describe a novel iterative formulation of a multi-output Gaussian process that can build and exploit a probabilistic model of the environmental variables being measured (including the correlations and delays that exist between them). We validate our approach using data collected from a network of weather sensors located on the south coast of England

Information Agents for Pervasive Sensor Networks

In this paper, we describe an information agent, that resides on a mobile computer or personal digital assistant (PDA), that can autonomously acquire sensor readings from pervasive sensor networks (deciding when and which sensor to acquire readings from at any time). Moreover, it can perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental parameters will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and we describe how we use an iterative formulation of a multi-output Gaussian process to build a probabilistic model of the environmental parameters being measured by local sensors, and the correlations and delays that exist between them. We validate our approach using data collected from a network of weather sensors located on the south coast of England

Mismatch distributions of mtDNA reveal recent human population expansions

Journal ArticleAlthough many genetic studies of human evolution have tried to make distinctions between the replacement and the multiregional evolution hypotheses, current methods and data have not resolved the issue. However, new advances in nucleotide divergence theory can complement these investigations with a description of human demographic behavior during the late Middle and Upper Paleolithic (approximately the last 250,000 years)

Genetic structure of ancient human populations

Journal ArticleDiscusses mitochondrial DNA (mtDNA) sequences as important source of data about the history of human species

Epigenetic remodelling of brain, body and behaviour during phase change in locusts

Abstract The environment has a central role in shaping developmental trajectories and determining the phenotype so that animals are adapted to the specific conditions they encounter. Epigenetic mechanisms can have many effects, with changes in the nervous and musculoskeletal systems occurring at different rates. How is the function of an animal maintained whilst these transitions happen? Phenotypic plasticity can change the ways in which animals respond to the environment and even how they sense it, particularly in the context of social interactions between members of their own species. In the present article, we review the mechanisms and consequences of phenotypic plasticity by drawing upon the desert locust as an unparalleled model system. Locusts change reversibly between solitarious and gregarious phases that differ dramatically in appearance, general physiology, brain function and structure, and behaviour. Solitarious locusts actively avoid contact with other locusts, but gregarious locusts may live in vast, migrating swarms dominated by competition for scarce resources and interactions with other locusts. Different phase traits change at different rates: some behaviours take just a few hours, colouration takes a lifetime and the muscles and skeleton take several generations. The behavioural demands of group living are reflected in gregarious locusts having substantially larger brains with increased space devoted to higher processing. Phase differences are also apparent in the functioning of identified neurons and circuits. The whole transformation process of phase change pivots on the initial and rapid behavioural decision of whether or not to join with other locusts. The resulting positive feedback loops from the presence or absence of other locusts drives the process to completion. Phase change is accompanied by dramatic changes in neurochemistry, but only serotonin shows a substantial increase during the critical one- to four-hour window during which gregarious behaviour is established. Blocking the action of serotonin or its synthesis prevents the establishment of gregarious behaviour. Applying serotonin or its agonists promotes the acquisition of gregarious behaviour even in a locust that has never encountered another locust. The analysis of phase change in locusts provides insights into a feedback circuit between the environment and epigenetic mechanisms and more generally into the neurobiology of social interaction.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Evaluation of terrain collision risks for flight style autonomous underwater vehicles

Photographic surveys of the seafloor with flight style autonomous underwater vehicles are a very effective tool for discovery and exploration. Due to the high terrain collision risk for the survey vehicle, they are employed with caution. The extent of this risk remains unquantified. For mission planning, researchers and vehicle operators have to rely on their experience. This paper introduces measures for vehicle risk and success and analyses how previously mapped terrains and artificially generated terrain maps can be used to categorize terrains. The developed measures are applied to a simulation of the Autosub6000 flight style AUV terrain following system. Based on quantitative parameters, changes to the obstacle avoidance system and survey mission plans can be better informed