Search results for "Decision process"
showing 10 items of 52 documents
A meta-cognitive architecture for planning in uncertain environments
2013
Abstract The behavior of an artificial agent performing in a natural environment is influenced by many different pressures and needs coming from both external world and internal factors, which sometimes drive the agent to reach conflicting goals. At the same time, the interaction between an artificial agent and the environment is deeply affected by uncertainty due to the imprecision in the description of the world, and the unpredictability of the effects of the agent’s actions. Such an agent needs meta-cognition in terms of both self-awareness and control. Self-awareness is related to the internal conditions that may possibly influence the completion of the task, while control is oriented t…
Comprehensive Uncertainty Management in MDPs
2013
Multistage decision-making in robots involved in real-world tasks is a process affected by uncertainty. The effects of the agent’s actions in a physical en- vironment cannot be always predicted deterministically and in a precise manner. Moreover, observing the environment can be a too onerous for a robot, hence not continuos. Markov Decision Processes (MDPs) are a well-known solution inspired to the classic probabilistic approach for managing uncertainty. On the other hand, including fuzzy logics and possibility theory has widened uncertainty representa- tion. Probability, possibility, fuzzy logics, and epistemic belief allow treating dif- ferent and not always superimposable facets of unce…
First results on applying a non-linear effect formalism to alliances between political parties and buy and sell dynamics
2016
We discuss a non linear extension of a model of alliances in politics, recently proposed by one of us. The model is constructed in terms of operators, describing the \emph{interest} of three parties to form, or not, some political alliance with the other parties. The time evolution of what we call \emph{the decision functions} is deduced by introducing a suitable hamiltonian, which describes the main effects of the interactions of the parties amongst themselves and with their \emph{environments}, {which are }generated by their electors and by people who still have no clear {idea }for which party to vote (or even if to vote). The hamiltonian contains some non-linear effects, which takes into…
Who are maximizers? Future oriented and highly numerate individuals
2015
Two studies investigated cognitive mechanisms that may be associated with people's tendency to maximize. Maximizers are individuals who are spending a great amount of effort in order to find the very best option in a decision situation, rather than stopping the decision process when they encounter a satisfying option. These studies show that maximizers are more future oriented than other people, which may motivate them to invest the extra energy into optimal choices. Maximizers also have higher numerical skills, possibly facilitating the cognitive processes involved with decision trade-offs.
Two Family Firms in Comparison: Ahlström and Schauman During the 20th Century
2006
Ahlstrom and Schauman are among the most prominent companies in Finnish industrial history, being family firms engaged in different branches of economic activity. At first both were mechanical wood processing companies, but diversified later into the pulp and paper industry as well. Ahlstrom is even still today an important paper producer, whilst Schauman merged in 1987 with the Kymmene Corporation, and is nowadays a part of the UPM-Kymmene Corporation. This paper analyses the strategic decision processes undertaken in the named companies during the 20 century. The companies were not the most typical ones in the Finnish wood processing industry, but were, perhaps, typical examples of old fa…
Allocation des ressources dans l’informatique en brouillard le calcul du brouillard véhiculaire pour une utilisation optimale des véhicules électriqu…
2019
Abstract: Technological advancements made it possible for Electric vehicles (EVs) to have onboard computation, communication, storage, and sensing capabilities. Nevertheless, most of the time these EVs spend their time in parking lots, which makes onboard devices cruelly underutilized. Thus, a better management and pooling these underutilized resources together would be strongly recommended. The new aggregated resources would be useful for traffic safety applications, comfort related applications or can be used as a distributed data center. Moreover, parked vehicles might also be used as a service delivery platform to serve users. Therefore, the use of aggregated abundant resources for the …
Weeds sampling for map reconstruction: a Markov random field approach
2012
In the past 15 years, there has been a growing interest for the study of the spatial repartition of weeds in crops, mainly because this is a prerequisite to herbicides use reduction. There has been a large variety of statistical methods developped for this problem ([5], [7], [10]). However, one common point of all of these methods is that they are based on in situ collection of data about weeds spatial repartition. A crucial problem is then to choose where, in the eld, data should be collected. Since exhaustive sampling of a eld is too costly, a lot of attention has been paid to the development of spatial sampling methods ([12], [4], [6] [9]). Classical spatial stochastic model of weeds cou…
Échantillonnage adaptatif optimal dans les champs de Markov, application à l’échantillonnage d’une espèce adventice
2012
This work is divided into two parts: (i) the theoretical study of the problem of adaptive sampling in Markov Random Fields (MRF) and (ii) the modeling of the problem of weed sampling in a crop field and the design of adaptive sampling strategies for this problem. For the first point, we first modeled the problem of finding an optimal sampling strategy as a finite horizon Markov Decision Process (MDP). Then, we proposed a generic algorithm for computing an approximate solution to any finite horizon MDP with known model. This algorithm, called Least-Squared Dynamic Programming (LSDP), combines the concepts of dynamic programming and reinforcement learning. It was then adapted to compute adapt…
Paths to purchase : the role of the online environment and the fluctuation of customer brand engagement
2016
Customers´ paths to purchase are constantly developing due to digitalization. Online channels enable customers to guide their own decision processes more than ever. When understanding the complex buying journeys, companies can gain competitive advantage. Another current and interesting phenomena in the field of marketing lies in a fairly new concept called customer brand engagement (CBE). The nature of CBE has been studied to some extent, but further research is needed, especially on fluctuation, since most research focuses on observing CBE levels during a specific context and time. The aim of this research is to create insight into the customer decision-making process and CBE. The focus is…
Critical Experiences During the Implementation of a Self-tracking Technology
2016
Emerging technologies have brought several new ways to track, measure and evaluate own activity. Well-being, nutrition, physical training, mood, and sleep are a few of the various measures that can be self-tracked by different technological solutions. At the same time, people are becoming more interested in themselves and their own well-being, and constant tracking of own activities is getting more and more popular both on individual level as well as in general healthcare. This study examines critical experiences that occur during the implementation phase of the innovation-decision process and their influence to adopting or rejecting a self-tracking technology. The study is qualitative in n…