An adaptive multi-agent system for self-organizing continuous optimization

Cette thèse présente une nouvelle approche pour la distribution de processus d'optimisation continue dans un réseau d'agents coopératifs. Dans le but de résoudre de tels problèmes, le domaine de l'optimisation multidisciplinaire a été proposé. Les méthodes d'optimisation multidisciplinaire proposent de distribuer le processus d'optimisation, généralement en reformulant le problème original d'une manière qui réduit les interconnexions entre les disciplines. Cependant, ces méthodes présentent des désavantages en ce qui concerne la difficulté de les appliquer correctement, ainsi que leur manque de flexibilité. En se basant sur la théorie des AMAS (Adaptive Multi-Agent Systems), nous proposent une représentation générique à base d'agents des problèmes d'optimisation continue. A partir de cette représentation, nous proposons un comportement nominal pour les agents afin d'exécuter le processus d'optimisation. Nous identifions ensuite certaines configurations spécifiques qui pourraient perturber le processus, et présentons un ensemble de comportements coopératifs pour les agents afin d'identifier et de résoudre ces configurations problématiques. Enfin, nous utilisons les mécanismes de coopération que nous avons introduit comme base à des patterns de résolution coopérative de problèmes. Ces patterns sont des recommandations de haut niveau pour identifier et résoudre des configurations potentiellement problématiques qui peuvent survenir au sein de systèmes de résolution collective de problèmes. Ils fournissent chacun un mécanisme de résolution coopérative pour les agents, en utilisant des indicateurs abstraits qui doivent être instanciés pour le problème en cours.In an effort to tackle such complex problems, the field of multidisciplinary optimization methods was proposed. Multidisciplinary optimization methods propose to distribute the optimization process, often by reformulating the original problem is a way that reduce the interconnections between the disciplines. However these methods present several drawbacks regarding the difficulty to correctly apply them, as well as their lack of flexibility. Based on the AMAS (Adaptive Multi-Agent Systems) theory, we propose a general agent-based representation of continuous optimization problems. From this representation we propose a nominal behavior for the agents in order to do the optimization process. We then identify some specific configurations which would disturb this nominal optimization process, and present a set of cooperative behaviors for the agents to identify and solve these problematic configurations. At last, we use the cooperation mechanisms we introduced as the basis for more general Collective Problem Solving Patterns. These patterns are high-level guideline to identify and solve potential problematic configurations which can arise in distributed problem solving systems. They provide a specific cooperative mechanism for the agents, using abstract indicators that are to be instantiated on the problem at hand

An interpretative phenomenological analysis of counselling psychologists' experiences of stress in NHS child and adolescent mental health tier 3 work settings

The aim of this study was to identify and understand counselling psychologists’ individual experiences of stress in NHS Child and Adolescent Mental Health Services Tier 3. The qualitative methodology of interpretative phenomenological analysis (IPA) was used to allow the emergence of each participant’s idiographic, personal experiences of the phenomenon of stress in their work settings, and the meaning each ascribed to it. Data was collected from seven counselling psychologists (six females, one male) permanently employment by NHS CAMHS. Each participant was individually interviewed on two separate occasions with a period of up to six months between interviews. Each semi-structured 60-minute interview was digitally timed, audio-recorded, transcribed in full, and analysed using IPA. All first interviews were conducted in person on NHS site locations. Some of the second interviews were done over Skype video at participants’ NHS sites or in person and the same protocol was observed as in the first interviews. Fourteen interviews were collected in total. A systematic analysis of the transcripts identified fourteen sub-themes which merged into four super-ordinate or master themes: (1) Impact of NHS changes on CAMHS Tier 3 work settings, (2) Therapy room impact, (3) Counselling psychologists’ well-being and morale, and (4) Professional identity issues. The findings showed that all the counselling psychologists were experiencing intense stress in their working lives. The study took place in the political context of National Health Service (NHS) reform and austerity based economic restructuring which is ongoing. Counselling psychologists believed such economic cuts caused contextual changes in CAMHS settings which brought new stressors into their working lives. Their experiences of stress were similar to factors consistently identified in organisational stress research as burnout risk factors or burnout itself. As a result of the increased stress, they expressed either a desire to leave their posts or they were already seeking work elsewhere. Participants also shared stress experiences related to professional identity issues involved in being the relatively new and only other psychology discipline working and competing for jobs in NHS CAMHS Tier 3. In many cases, a mitigating factor of the stress was a sense of meaning derived from their relationships and work with mentally unwell young people. Given the importance of the therapeutic relationship as a conduit for successful therapeutic outcomes, research on how best to support and protect against occupational stress experienced as impacting the early intervention work of NHS CAMHS counselling psychologists is an area for future research

JFPC 2019 - Actes des 15es Journées Francophones de Programmation par Contraintes

National audienceLes JFPC (Journées Francophones de Programmation par Contraintes) sont le principal congrès de la communauté francophone travaillant sur les problèmes de satisfaction de contraintes (CSP), le problème de la satisfiabilité d'une formule logique propositionnelle (SAT) et/ou la programmation logique avec contraintes (CLP). La communauté de programmation par contraintes entretient également des liens avec la recherche opérationnelle (RO), l'analyse par intervalles et différents domaines de l'intelligence artificielle.L'efficacité des méthodes de résolution et l'extension des modèles permettent à la programmation par contraintes de s'attaquer à des applications nombreuses et variées comme la logistique, l'ordonnancement de tâches, la conception d'emplois du temps, la conception en robotique, l'étude du génôme en bio-informatique, l'optimisation de pratiques agricoles, etc.Les JFPC se veulent un lieu convivial de rencontres, de discussions et d'échanges pour la communauté francophone, en particulier entre doctorants, chercheurs confirmés et industriels. L'importance des JFPC est reflétée par la part considérable (environ un tiers) de la communauté francophone dans la recherche mondiale dans ce domaine.Patronnées par l'AFPC (Association Française pour la Programmation par Contraintes), les JFPC 2019 ont lieu du 12 au 14 Juin 2019 à l'IMT Mines Albi et sont organisées par Xavier Lorca (président du comité scientifique) et par Élise Vareilles (présidente du comité d'organisation)

Agent-Driven Representations, Algorithms, and Metrics for Automated Organizational Design.

As cooperative multiagent systems (MASs) increase in interconnectivity, complexity, size, and longevity, coordinating the agents' reasoning and behaviors becomes increasingly difficult. One approach to address these issues is to use insights from human organizations to design structures within which the agents can more efficiently reason and interact. Generally speaking, an organization influences each agent such that, by following its respective influences, an agent can make globally-useful local decisions without having to explicitly reason about the complete joint coordination problem. For example, an organizational influence might constrain and/or inform which actions an agent performs. If these influences are well-constructed to be cohesive and correlated across the agents, then each agent is influenced into reasoning about and performing only the actions that are appropriate for its (organizationally-designated) portion of the joint coordination problem. In this dissertation, I develop an agent-driven approach to organizations, wherein the foundation for representing and reasoning about an organization stems from the needs of the agents in the MAS. I create an organizational specification language to express the possible ways in which an organization could influence the agents' decision making processes, and leverage details from those decision processes to establish quantitative, principled metrics for organizational performance based on the expected impact that an organization will have on the agents' reasoning and behaviors. Building upon my agent-driven organizational representations, I identify a strategy for automating the organizational design process~(ODP), wherein my ODP computes a quantitative description of organizational patterns and then searches through those possible patterns to identify an (approximately) optimal set of organizational influences for the MAS. Evaluating my ODP reveals that it can create organizations that both influence the MAS into effective patterns of joint policies and also streamline the agents' decision making in a coordinate manner. Finally, I use my agent-driven approach to identify characteristics of effective abstractions over organizational influences and a heuristic strategy for converging on a good abstraction.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113616/1/jsleight_1.pd

Behavioral Economics - Enhanced: Machine Learning and Decision Making

In this thesis, I investigate decision-making in the fields of behavioral economics, experimental economics, and law and economics. The research questions I ask are: Can we nudge people towards being more honest? Can we use language to find out who lies? Which factors influence a judge’s decision, and how do people cooperate? Specifically, I investigate contributions in a public goods game, (dis-)honest decision-making in a die-in-the-cup and tax compliance game. Furthermore, I investigate the bounds of rational decision-making in the context of the law. To answer the posed questions, I apply – alongside traditional econometrics – machine learning methods: I use natural language classification to predict decisions based on text data. Furthermore, I use time-series clustering to reduce complexity and thereby enable theory building and interpretation

10 Years Barometer for Public Real Estate in the Netherlands

2007, the Ministry of Housing and Spatial Planning took the initiative to issue the social building blocks: real estate for facilities. This has been the first attempt to deal with social real estate professionally as an asset. In 2008 the professorship of public real estate started with its first Barometer for Social Real Estate. In 2009, I advocated in Real Estate Magazine that research into social real estate is necessary from the perspective of Corporate Real Estate Management (CREM) through new development models and more (PhD) research. In anticipation of the municipal elections of 2010, research by the research group Municipal Real Estate showed that social real estate was not a matter for the election programs of the political parties. This was a prelude to the funded RAAK subsidy application towards marketed municipal real estate for carrying out practice-oriented research. In 2012, this research led to the externally funded research group Social Real Estate. After that, the Social Real Estate professorship profiled itself in different areas. Extra media publicity has been generated primarily thanks to the attention of minister Stef Blok in 2014, when he received the first copy of the book Barometer Maatschappelijk Vastgoed (Social Real Estate): Corporate Social Responsibility at our annual congress, the round table meeting with State Secretary for Health, Welfare and Sport Martin van Rijn in 2015 and the informal conversation with the Minister of Education, Culture and Science Jet Bussemaker in 2015, as well as the many publications of the lectorate. In the 2016 debate with civil society with the Prime Minister Mark Rutte when handing over the book Barometer Maatschappelijk Vastgoed (Social Real Estate) 2016, a round table meeting in 2017 with Minister of Home Affairs and Kingdom Relations Stef Blok, aldermen and directors Real Estate of Municipalities in The Netherlands, have contributed to social and economic knowledge utilization for future and existing real estate professionals. At the PROVADA 2017 we co-organized ‘Shrink: Emptiness and Space for Innovation and Change’ session, where the Minister of the Home Affairs and Kingdom Relations Ronald Plasterk presented his vision on this subject