Genetic algorithms for shortest path routing
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1) A genetic algorithm starts with a population of random solutions called chromosomes.
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3) The algorithm iterates, applying the genetic operators to successive generations, until an optimal solution emerges or a stopping criteria is met. Genetic algorithms can find multiple optimal solutions and do not require additional information beyond the fitness
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Knowledge Based Genetic Algorithm for Robot Path Planning
Knowledge Based Genetic Algorithm for Robot Path Planning
Review And Evaluations Of Shortest Path Algorithms
Review And Evaluations Of Shortest Path Algorithms
Solving the traveling salesman problem by genetic algorithm
Solving the traveling salesman problem by genetic algorithm
Travelling salesman problem using genetic algorithms
Travelling salesman problem using genetic algorithms
Dernier
De l'IA comme plagiat à la rédaction d'une « charte IA » à l'université
L'IA connaît une croissance rapide et son intégration dans le domaine éducatif soulève de nombreuses questions. Aujourd'hui, nous explorerons comment les étudiants utilisent l'IA, les perceptions des enseignants à ce sujet, et les mesures possibles pour encadrer ces usages.
Constat Actuel
L'IA est de plus en plus présente dans notre quotidien, y compris dans l'éducation. Certaines universités, comme Science Po en janvier 2023, ont interdit l'utilisation de l'IA, tandis que d'autres, comme l'Université de Prague, la considèrent comme du plagiat. Cette diversité de positions souligne la nécessité urgente d'une réponse institutionnelle pour encadrer ces usages et prévenir les risques de triche et de plagiat.
Enquête Nationale
Pour mieux comprendre ces dynamiques, une enquête nationale intitulée "L'IA dans l'enseignement" a été réalisée. Les auteurs de cette enquête sont Le Sphynx (sondage) et Compilatio (fraude académique). Elle a été diffusée dans les universités de Lyon et d'Aix-Marseille entre le 21 juin et le 15 août 2023, touchant 1242 enseignants et 4443 étudiants. Les questionnaires, conçus pour étudier les usages de l'IA et les représentations de ces usages, abordaient des thèmes comme les craintes, les opportunités et l'acceptabilité.
Résultats de l'Enquête
Les résultats montrent que 55 % des étudiants utilisent l'IA de manière occasionnelle ou fréquente, contre 34 % des enseignants. Cependant, 88 % des enseignants pensent que leurs étudiants utilisent l'IA, ce qui pourrait indiquer une surestimation des usages. Les usages identifiés incluent la recherche d'informations et la rédaction de textes, bien que ces réponses ne puissent pas être cumulées dans les choix proposés.
Analyse Critique
Une analyse plus approfondie révèle que les enseignants peinent à percevoir les bénéfices de l'IA pour l'apprentissage, contrairement aux étudiants. La question de savoir si l'IA améliore les notes sans développer les compétences reste débattue. Est-ce un dopage académique ou une opportunité pour un apprentissage plus efficace ?
Acceptabilité et Éthique
L'enquête révèle que beaucoup d'étudiants jugent acceptable d'utiliser l'IA pour rédiger leurs devoirs, et même un quart des enseignants partagent cet avis. Cela pose des questions éthiques cruciales : copier-coller est-il tricher ? Utiliser l'IA sous supervision ou pour des traductions est-il acceptable ? La réponse n'est pas simple et nécessite un débat ouvert.
Propositions et Solutions
Pour encadrer ces usages, plusieurs solutions sont proposées. Plutôt que d'interdire l'IA, il est suggéré de fixer des règles pour une utilisation responsable. Des innovations pédagogiques peuvent également être explorées, comme la création de situations de concurrence professionnelle ou l'utilisation de détecteurs d'IA.
Conclusion
En conclusion, bien que l'étude présente des limites, elle souligne un besoin urgent de régulation. Une charte institutionnelle pourrait fournir un cadre pour une utilisation éthique.
Le Comptoir OCTO - Équipes infra et prod, ne ratez pas l'embarquement pour l'...
par Claude Camus (Coach agile d'organisation @OCTO Technology) et Gilles Masy (Organizational Coach @OCTO Technology)
Les équipes infrastructure, sécurité, production, ou cloud, doivent consacrer du temps à la modernisation de leurs outils (automatisation, cloud, etc) et de leurs pratiques (DevOps, SRE, etc). Dans le même temps, elles doivent répondre à une avalanche croissante de demandes, tout en maintenant un niveau de qualité de service optimal.
Habitué des environnements développeurs, les transformations agiles négligent les particularités des équipes OPS. Lors de ce comptoir, nous vous partagerons notre proposition de valeur de l'agilité@OPS, qui embarquera vos équipes OPS en Classe Business (Agility), et leur fera dire : "nous ne reviendrons pas en arrière".
MongoDB in a scale-up: how to get away from a monolithic hell — MongoDB Paris...
This is the slide deck of a talk by Alexis "Horgix" Chotard and Laurentiu Capatina presented at the MongoDB Paris User Group in June 2024 about the feedback on how PayFit move away from a monolithic hell of a self-hosted MongoDB cluster to managed alternatives. Pitch below.
March 15, 2023, 6:59 AM: a MongoDB cluster collapses. Tough luck, this cluster contains 95% of user data and is absolutely vital for even minimal operation of our application. To worsen matters, this cluster is 7 years behind on versions, is not scalable, and barely observable. Furthermore, even the data model would quickly raise eyebrows: applications communicating with each other by reading/writing in the same MongoDB documents, documents reaching the maximum limit of 16MiB with hundreds of levels of nesting, and so forth. The incident will last several days and result in the loss of many users. We've seen better scenarios.
Let's explore how PayFit found itself in this hellish situation and, more importantly, how we managed to overcome it!
On the agenda: technical stabilization, untangling data models, breaking apart a Single Point of Failure (SPOF) into several elements with a more restricted blast radius, transitioning to managed services, improving internal accesses, regaining control over risky operations, and ultimately, approaching a technical migration when it impacts all development teams.
PRESENTATION DE L'ACTIVE DIRECTORY SOUS WINDOWS SERVEUR.pptx
Active Directory est le service d'annuaire développé par Microsoft pour la gestion des identités et des accès dans les environnements Windows
Ouvrez la porte ou prenez un mur (Agile Tour Genève 2024)
(Conférence dessinée)
Vous êtes certainement à l’origine, ou impliqué, dans un changement au sein de votre organisation. Et peut être que cela ne se passe pas aussi bien qu’attendu…
Depuis plusieurs années, je fais régulièrement le constat de l’échec de l’adoption de l’Agilité, et plus globalement de grands changements, dans les organisations. Je vais tenter de vous expliquer pourquoi ils suscitent peu d'adhésion, peu d’engagement, et ils ne tiennent pas dans le temps.
Heureusement, il existe un autre chemin. Pour l'emprunter il s'agira de cultiver l'invitation, l'intelligence collective , la mécanique des jeux, les rites de passages, .... afin que l'agilité prenne racine.
Vous repartirez de cette conférence en ayant pris du recul sur le changement tel qu‘il est généralement opéré aujourd’hui, et en ayant découvert (ou redécouvert) le seul guide valable à suivre, à mon sens, pour un changement authentique, durable, et respectueux des individus! Et en bonus, 2 ou 3 trucs pratiques!
COURS D'ADMINISTRATION RESEAU SOUS WINDOWS
cette présentation contient le contenu minimum pour l'Administration de Réseau Local sous Windows
Le Comptoir OCTO - Qu’apporte l’analyse de cycle de vie lors d’un audit d’éco...
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Sur un exemple très concret d’audit d’éco-conception de l’outil de bilan carbone C’Bilan développé par ICDC (Caisse des dépôts et consignations) nous allons expliquer en quoi l’ACV (analyse de cycle de vie) a été déterminante pour identifier les pistes d’actions pour réduire jusqu'à 82% de l’empreinte environnementale du service.
Vidéo Youtube : https://www.youtube.com/watch?v=7R8oL2P_DkU
Compte-rendu :
Le support de présentation des Signaux 2024
Découvrez le support de présentation des Signaux 2024, la conférence des grandes tendances de l'innovation et du numérique.
Dernier (9)
De l'IA comme plagiat à la rédaction d'une « charte IA » à l'université
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PRESENTATION DE L'ACTIVE DIRECTORY SOUS WINDOWS SERVEUR.pptx
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Le Comptoir OCTO - Qu’apporte l’analyse de cycle de vie lors d’un audit d’éco...
Genetic algorithms for shortest path routing
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- 26. 4.5 4 3.5 COMPUTATION TIME 3 2.5 Dijistkra 2 Genetic 1.5 Algorithm 1 0.5 0 15 20 25 30 35 40 45 50 No OF NODES 26
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Notes de l'éditeur
- Crossover probability describes how often crossover would be performed.If no crossover the new off springswould be exact copies of parents
- Example of one point crossover ..Crossover from the 9th bit
- 10000 shows impossible paths/ non pathsOther values are costs associated with a path
- Crossover probability is the measure of how often crossover would be performed.More than 0.5 is optimum
- Mutation probability (or ratio) is basically a measure of the likeness that random elements of your chromosome will be flipped into something else
- There may be change in topology of network as some nodes may join the network or some nodes may leave the network or some nodes may fail. Under these circumstances the optimal path may no more be the shortest.Hence the network has to be refreshed at every t secondsand new routes may be generated
- Reached optimum after 29th run