If new facts are carelessly added, Ψ may become inconsistent. To avoid this we have defined an updating process  that removes any element of Ψ contradicting the new observation. Note that according to our criterion, new perceptions are always preferred over older ones. There is a simple reason behind this policy: given our initial assumption, both ofthe observations in disagreement were correct at the time of their assimilation. As a result, the only explanation for the conflict is a change inthe state of world, and the new fact should be favored since it reflects the actual state. It is worth mentioning that by updating the set of observations the agent can modify its beliefs, changing its previous picture ofthe world when faced with new information.
Description Logics (DL)  are a family of knowledge representation formalisms based onthe notions of concepts (unary predicates, classes) and roles (binary relations) that allow to build complex concepts and roles from atomic ones. Let C, D stand for concepts, R for a role and a, b for individuals. Concept descrip- tions are built from concept names using the constructors conjunction (C � D), disjunction (C �D), complement (¬C ), existential restriction (∃R.C), and value restriction (∀R.C). To deﬁne the semantics of concept descriptions, concepts are interpreted as subsets of a domain of interest, and roles as binary relations over this domain. Further extensions are possible including inverse (P − ) and tran-
In general the conditions of an optimization problem changes by one ofthe following reasons or a combination of both : 1) The objective function changes itself, 2) The constraints change. A change inthe objective function appears when the purpose ofthe problem changes. Here conditions which were considered desirable before can turn out to be undesirable now and vice versa. Changes in constraints, which modify feasibility of solutions, are related to resources and their availability. Changes can be small or big, soft or abrupt, chaotic, etc. When changes are big, abrupt or chaotic the similarity between solutions found so far and the new ones can be worthless. Even under these hard environments Evolutionary Computation (EC) offers advantages, which are absent in other heuristics when searching for solutions to non-stationary problems. The main advantage relies inthe fact that Evolutionary Algorithms (EAs) keep a population of solutions. Consequently, facing the change, they allow moving from a solution to another one to determine if any of them are of merit to continue the search from them instead of from scratch . Goldberg and Smith , Cobb and Grefenstette  initiated the research related to the behaviour of EAS ondynamic fitness functions between 1987 and 1992. Recently the interest in this area was dramatically incremented , , , , , , , , , and . The following sections are organized as follows. Section 2 presents a definition ofdynamicenvironments studied in this work. Section 3 describes thedynamic test functions used. Section 4 describes the EA. In section 5 the experiments performed are described. In section 6 results are discussed and finally this document shows our conclusions, current and future work.
Since 2008, the British government has sponsored the Fore- sight Project on Mental Capital and Wellbeing in order to identify the characteristics of human capital needed to deal with highly competitive economies inthe world (Bedding- ton et al., 2008). According to the committee of this project, involving around 450 specialists from several knowledge fields, mental capital refers to people’s cognitive abilities and flexible learning, while wellbeing refers to the ability of individuals in engaging productively and positively in their community and finding strategies to develop their potential. Both human capital and wellbeing are individual psycholog- ical factors related and developed during the childhood and adolescence. They serve as the cornerstones of quality of life in adulthood. The goal ofthe British project is to identify the new skills developed in lifelong due to new technology and work inthe information age (UK Government Office for Science, 2016). In order to achieve this goal, the current skills inthe UK population will be mapped and compared to those that are needed over the next 10 or 20 years.
Regarding the evidence from mathematical models and experiments, it is clear that temperature mean and vari- ability could affect thedynamic behavior ofthe LPA model in a slightly more complex way than inthe Ricker model. If cannibalism of eggs by larvae is zero, then inthe first scenario the LPA model could be destabilized for popula- tions located to the left side ofthe maximum b value (from stable equilibrium to two-point cycle), but have a stabilizing effecton populations located to the right side. Inthe second scenario, theeffectof an increase in thermal variability on b could have a destabilizing effecton populations located to the left side ofthe inflection point, but a stabilizing effecton populations located to the right side. Inthe third scenario, theeffectof an increase in average temperature and variability on b could have a destabilizing effecton populations located to the left side ofthe inflection point, a stabilizing effecton populations located between the maximum b value and the upper limit, and a mixed effect between the inflection point and the maximum b value, where the net effect will depend onthe relative magnitude ofthe changes in average and variance. Inthe case of adult survival (1 – m a ), the situ-
Innovativeness is a very common practice among craft businesses, and in an environment of economic decline, social turbulence, and natural events, an emphasis onthe production RI GLIIHUHQWLDWHG SURGXFWV ZLWK LPSURYHG design and quality, can positively modify business performance. In addition, a proactive posture focused on protecting market share, by cautiously managing product and market LQIRUPDWLRQ DV ZHOO DV WKH GHYHORSPHQW DQG FUHDWLRQRIQHZSURGXFWGHVLJQVKDVEHQH¿FLDO results, as these practices positively affect EXVLQHVV SUR¿WDELOLW\ 2Q WKH RWKHU KDQG a reduction in price-based competition is UHFRPPHQGDEOHDVYHU\ORZSULFHVDQGKHDY\ discounts lead to very marginal earnings that EDUHO\DOORZIRUWKHUHFXSHUDWLRQRILQYHVWPHQW inthe business. It is not surprising that craft businesses that implement a combination of these three practices are able to adapt to FKDQJLQJ HQYLURQPHQW FRQGLWLRQV DQG EHQH¿W from improved business results. Moreover, the entrepreneurs of such businesses perceive a JUHDWHU VHQVH RI VDWLVIDFWLRQ ZLWK WKHLU ZRUN and lifestyle.
In control systems a representation ofthe physical process which is to be controlled is needed in order to calculate control signals and keep the system stable. Networked Control Systems (NCS) are a special case of control systems where network-induced delays make the system stochastic and hard to predict. Pattern recognition techniques have been extensively used in learning the behavior of processes that present a certain degree of stochastic behavior. The Quality of Control (QoC) of each closed-loop system in a Networked Control System is strongly affected by the network-induced delay produced by sensors and control signals. Controller Area Network (CAN) is a popular real-time ﬁeld-bus used for small-scale distributed environments such as automobiles. In CAN the delay exhibits a stochastic behavior and varies according to the network load. Since QoC is affected by delays, designing and evaluating a controller must take into account theeffectof network-induced delays. A continuous Hidden Markov Model (HMM) for CAN network-induced delays is illustrated. The model plays the role of a classiﬁer and an estimator; based on delay observations, the model can estimate the network load and predict future time delay values. The model was trained/tested using experimental data taken from a real CAN system with excellent results.
We are interesting inthe modelling ofreasoning mechanisms that include emotions as relevant conductors. In this work we present an approach to emo- tional reasoning for believable agents, by introducing a mechanism to progres- sively build a map ofdefeasible knowledge for reasoning. Since emotions may affect reasoning and reasoning may affect emotions, the highlighted knowledge evolves trough time. In this approach, a logic program is used to represent the knowledge ofthe agent, and thereasoningofthe agent is presented as the evolu- tion of an inference graph similar to those used in various works in TMS , and argumentation [8, 11, 9]. This work is based onthe formalism presented in , but instead of using abstract arguments as information pieces, we add more detail by the specification ofthe agent’s knowledge as a set of inference rules, what allows us to model thereasoning process more closely to a incoming implementation.
In a DGS a similar situation to that described in paper and pencil occurs when the solver constructs a figure with a robust property (Healy, 2000) while mentally imposing on it a contradictory property without a robust construction. By robust construction in a DGS, we mean a construction that can keep the de- sired properties of a figure invariant under dragging. What happens if, instead, the solver attempts to construct both properties robustly? However, the solver may be uncertain whether such a construction is possible or not, or s/he may real- ize the impossibility when interpreting the DGS’ feedback. Such feedback in- cludes the making explicit, robustly, of all properties that are derived from the properties constructed robustly during the construction steps ofthe figure. This is the case we find particularly interesting. In this paper we report on ways of rea- soning that seem to be induced by the feedback provided by the DGS.
Note that the counterargument relationship (def. 4.3) is defined in terms of contradic- tion. Therefore certainty factors should play no role in determining whether an argument counterargues another. In LDS AR , the usual criterion for defeat among arguments is speci- ficity [SL92]. However, in LDS ∗ AR defeat can rely onthe numerical weight ofthe arguments in conflict. For example, an argument A:h could be deemed as a proper defeater B:q if cf (A:h) > cf (B:q). Similarly, a blocking defeat situation would arise if cf (A:h) = cf (B:q), or alternatively | cf (A:h) − cf (B:q) |≤ ǫ, for ǫ arbitrarily small. It is interesting to note that an aggregated preference criterion ∗
This study presented some limitations and results should be taken cautiously. A greater number of subjects could shed light onthe influence of static foot posture ondynamic stiffness during the early and late midstance phases. The results are limited to the description ofthe mechanical behaviour of adult male subjects, and further research should focus on children, adolescents or the elderly. Also, it might be interesting to study theeffectofthe foot type in women, as they are especially susceptible to changes in joint flexibility . The data reported for midtarsal and metatarsophalangeal joints does not allow the analysis of a particular joint. And finally, the tangential components ofthe ground reaction force were neglected. Anyway, their effectonthe flexion moments is small because their magnitudes are much smaller than those ofthe normal component  and also the moment arms, as we checked (results not shown for brevity), so that the moment graphs reported here for the normal FPI sample are very close to those reported in previous works  that took into account the tangential components.
Theeffectof morphological lesion parameters and partial volume issues on diagnostic performance was not investi- gated in this study. This, in combination with the fact that an ideal observer was used, means that the estimated AUC values should not be interpreted as expected performance inthe clinic. Rather, results should be interpreted in terms of relative performance differences between protocols for the selected object model and consideration of kinetic information only. The fact that the simulated speciﬁcity ofthe protocols was lower than the speciﬁcity typically seen inthe clinic is probably due to the lack of inclusion of morphological information. Inthe future, if considera- tions of lesion morphology are included, this framework could be expanded to allow more general optimizations of breast MRI protocols that include spatial resolution and region-of-interest size and placement.
When introducing numerical values for modeling uncertainty, extensional and inten- sional approaches can be distinguished. Extensional approaches treat uncertainty as a generalized truth value attached to formulas. Computing the uncertainty of any formula is a function ofthe uncertainties of its subformulas. Intensional approaches, onthe other hand, are model-based: uncertainty is attached to \states of a®airs" or subsets of \possi- ble worlds". Typical examples of this extensional approaches are production systems and rule-based systems.
̶ Social turbulence as a result ofthe 2006 social-political movement in Oaxaca. The social turbulence affected the activities of various economic sectors, but mostly the traditional crafts sector (Martínez, 2008; Zafra, 2008; Hernández et al., 2010) due to the unstable environment created by street blockades, mass marches and protests, and the closing of governmental offices, which significantly affected both safety and social coexistence (Sorroza, 2008). The systematic presence of those social disruptions, even after four years ofthe aforementioned movement, along with public insecurity resulting from violence associated with the struggle against organized crime, negatively affected the performance of craft businesses by generating unfavorable conditions for the commercialization of their products (Chabela, 2011).
was set to 0.2, and the augmented probabilities of crossover and mutation were fixed at 0.5 and 0.8, respectively. Tournament size was the 10% of population size. The percentage of random immigrants was set to 30% ofthe population. Immigrants are inserted when a change was produced. The individuals to be replaced by immigrants are randomly selected with equal probability. A number of experiments were designed differing inthe function selected and inthe severity ofthe changes to perform on it. For each of these experiments 30 runs were performed with distinct initial population.
Let us delve a bit into this apparent contradiction (that is, having a sensible framework for KR&R which fails to uphold cut, cautious monotonicity, or both). It can be argued that defeasible argumen- tation has evolved inthe last twenty years as a successful approach for modelling commonsense rea- soning. With several formalism reported inthe literature reaching a mature state [16, 14, 13, 5, 7, 2], research in this field has played a major role inthe development and deployment of solutions to tough, complex real world problems involving varying degrees of common-sense reasoning, such as mediation framework for supporting decision making in groups , intelligent systems used in med- ical research , or providing proactive assistance for natural language usage assessment . We refer the interested reader to the comprehensive survey of applications built around argumentation frameworks compiled by Carbogim et al. .
In this work, we are going to present a framework to deal with learning in distributed data, based on multi-agent systems, and where we are interested in using multiple models ofthe data. Moreover, due to the open and dynamic nature of multi-agent systems, we are interested in Lazy Learning techniques, and specially Case-Based Reasoning (CBR) . Lazy learning techniques are better suited for open and dynamic systems than eager learning techniques, since they are not sensitive to changes inthe data, while eager learning techniques have to rebuild (or adapt) their models ofthe data every time that data changes. Case-Based Reasoning (CBR) is a specific type of lazy learning, that consists of storing problem solving experiences (called cases) so that they can be reused to solve future problems. CBR basically relies onthe assumption that similar problems require similar solutions. A typical CBR system solves a problem by retrieving cases stored in its case memory (called the case base) that are similar to the problem at hand, and reusing the solution ofthe retrieved cases to solve the problem. Once the proposed solution for the new problem has been revised, a new case is created and it can be retained inthe case base. This problem solving cycle is known as the R4 model , that divides the activity of a CBR system in four processes: retrieve, reuse, revise, and retain.
become available or information we used to count on with is no longer available or valid). Usually incom- plete information appears in any way ofreasoning be- cause its very difficult to represent absolutely all the information related to the objects we count on. As a matter of fact there are systems such as Situation Calculus  where this problem is clear. Any time information about a new entity becomes available we must revise all the axioms onthe representation. Ar- gumentative Systems’s devolvement is based on previ- ous research on Logic Programming, Nonmonotonic Reasoning. Argumentation has obtained important re- sults, providing powerful tools for knowledge repre- sentation and some aspects of Commonsense reason- ing. In this sense DeLP  was developed. DeLP is a formalism that combines results of Logic Program- ming and Defeasiblereasoning.
The contribution of this paper is three-fold: (i) it consolidates research re- sults onthe δ-ontology framework presented previously by G´ omez et al. [7,8] and G´ omez and Simari , (ii) it discusses how some historical problems inin- heritance networks  are solved in δ-ontologies and, finally, (iii) it shows how issues inreasoning with argumentation frameworks based on Dung’s grounded semantics are also solved inthe δ-ontologies framework. Our research method- ology includes the gathering of representative examples inthe literature and showing how the δ-ontologies framework handles the problem of instance check- ing in these examples. In brief, this contribution reaffirms the results of previous work and can be considered an expansion of past work inthe field.