Imagine the following situation. You give your favorite robot, named Pippi, the task to fetch a heavy parcel that just arrived at your front door. While pushing the parcel back to you, she must travel through a door. Unfortunately, the parcel she is pushing is blocking her camera, giving her a hard time to see the door. If she cannot see the door, she cannot safely push the parcel through it. What would you as a human do in a similar situation? Most probably you would ask someone for help, someone to guide you through the door, as we ask for help when we need to park our car in a tight parking spot. Why not let the robots do the same? Why not let robots help each other? Luckily for Pippi, there is another robot, named Emil, vacuum cleaning the floor in the same room. Since Emil has a video camera and can view both Pippi and the door at the same time, he can estimate Pippi's position relative to the door and use this information to guide Pippi through the door by wireless communication. In that way he can enable Pippi to deliver the parcel to you. The goal of this thesis is to endow robots with the ability to help each other in a similar way. More specifically, we consider distributed robot systems in which: (1) each robot includes modular functionalities for sensing, acting and/or processing; and (2) robots can help each other by offering those functionalities. A functional configuration of such a system is any way to allocate and connect functionalities configuration among the robots. An interesting feature of a system of this type is the possibility to use different functional configurations to make the same set of robots perform different tasks, or to perform the same task under different conditions. In the above example, Emil is offering a perceptual functionality to Pippi. In a different situation, Emil could offer his motion functionality to help Pippi push a heavier parcel. In this thesis, we propose an approach to automatically generate, at run time, a functional configuration of a distributed robot system to perform a given task in a given environment, and to dynamically change this configuration in response to failures. Our approach is based on artificial intelligence planning techniques, and it is provably sound, complete and optimal. In order to handle tasks that require more than one step (i.e., one configuration) to be accomplished, we also show how methods for automatic configuration can be integrated with methods for task planning to produce a complete plan were each step is a configuration. For the scenario above, generating a complete plan before the execution starts enables Pippi to know before hand if she will be able to get the parcel or not. We also propose an approach to merge configurations, which enables concurrent execution of configurations, thus reducing execution time. We demonstrate the applicability of our approach on a specific type of distributed robot system, called Peis-Ecology, and show experiments in which configurations and sequences of configurations are automatically generated and executed on real robots. Further, we give an experiment where merged configurations are created and executed on simulated robots.

As more robots and sensors are deployed in work and home environments, there is a growing need for these devices to act with some degree of autonomy to fulfill their purpose. Automated planning can be used to synthesize plans of action that achieve this. The main challenge addressed in this thesis is to consider how the automated planning problem changes when considered in the context of environments that are populated by humans. Humans have their own plans, and automatically generated plans should not interfere with these. We refer to this as social acceptability. Opportunities for proactive behavior often arise during execution. The planner should be able to identify these opportunities and proactively plan accordingly. Both social acceptability and proactivity require the planner to identify relevant situations from available information. We refer to this capability as context-awareness, and it may require complex inferences based on observed human activities. Finally, planning may have to consider cooperation with humans to reach common goals or to enable robots and humans to support one another. This thesis analyzes the requirements that emerge from human-aware planning — what it takes to make automated planning socially acceptable, proactive, context aware, and to make it support cooperation with humans. We formally state the human-aware planning problem, and propose a planning and execution framework for human-aware planning that is based on constraint reasoning and flaw-resolution techniques, and which fulfills the identified requirements. This approach is modular and extendable: new types of constraints can be added and solvers can be exchanged and re-arranged. This allows us to address the identified requirements for humanaware planning. In particular, we introduce Interaction Constraints (ICs) for this purpose, and propose patterns of Ics for social acceptability, proactivity, and contextawareness. We also consider cooperative plans in which certain actions are assigned to humans and the implications that this has. We evaluate the proposed methods and patterns on a series of use cases, as well as a variety of domains including a real-world robotic system. We evaluate the proposed methods and patterns on a series of use cases, as well as a variety of domains including a real-world robotic system. introduce Interaction Constraints (ICs) for this purpose, and propose patterns of ICs for social acceptability, proactivity, and context-awareness. We also consider cooperative plans in which certain actions are assigned to humans and the implications that this has. We evaluate the proposed methods and patterns on a series of use cases, as well as a variety of domains including a real-world robotic system.

It is often beneficial for an autonomous agent that operates in a complex environment to make use of different types of mathematical models to keep track of unobservable parts of the world or to perform prediction, planning and other types of reasoning. Since a model is always a simplification of something else, there always exists a tradeoff between the model’s accuracy and feasibility when it is used within a certain application due to the limited available computational resources. Currently, this tradeoff is to a large extent balanced by humans for model construction in general and for autonomous agents in particular. This thesis investigates different solutions where such agents are more responsible for balancing the tradeoff for models themselves in the context of interleaved task planning and plan execution. The necessary components for an autonomous agent that performs its abstractions and constructs planning models dynamically during task planning and execution are investigated and a method called DARE is developed that is a template for handling the possible situations that can occur such as the rise of unsuitable abstractions and need for dynamic construction of abstraction levels. Implementations of DARE are presented in two case studies where both a fully and partially observable stochastic domain are used, motivated by research with Unmanned Aircraft Systems. The case studies also demonstrate possible ways to perform dynamic abstraction and problem model construction in practice. / <p>Report code: LiU-Tek-Lic-2008:21.</p>

This study is directed to the problem of the quantitative determination of the number of additional personnel required in an organization for servicing unscheduled priority tasks without delaying the completion of scheduled tasks. The manager of an organization which has been enlarged in order to respond adequately to the random arrival of priority requests may face criticism if the organization appears to be "overstaffed" during periods when only "routine" service requirements must be met. An audit team oriented toward accounting-type data may be reluctant to accept a manager's justification of his organization's size if the justification is based primarily on nonquantitative arguments.

Pre-writing strategies are conscious thoughts, actions, or behaviors used by writers when they plan before writing. Research in second language writing suggests that specific writing strategies related to writing purposes, audience, brainstorming, and organizing ideas are teachable and have a potential to improve the quantity and quality of writing produced by English as second language (ESL) learners. This study investigated the effects of computer-based pre-writing strategy training guided by procedural facilitation (Bereiter & Scardamalia, 1987) on intermediate ESL students' writing strategy use, writing quantity, and writing quality. A sequential mixed methods design was utilized with an initial quasi-experimental phase followed by semi-structured interviews. Forty-one participants from four intact intermediate-writing classes in an intensive English program participated in the quasi-experimental phase of the study. The classes were randomly assigned into two control and two experimental groups. The instructional modules for the control groups included writing instruction related to paragraph writing, essay writing, and opinion essays whereas the training modules for the experimental groups consisted of pre-writing strategies related to writing purposes, audience, and idea generation and organization. In addition, the experimental groups were trained to generate and organize ideas using Inspiration 6, an idea graphic organizer software program. The participants' writing performances and uses of pre-writing strategies prior to and after the training were analyzed. In addition, six semi-structured interviews conducted shortly after the post-test helped to illuminate the quantitative results. Results demonstrate a significant training impact on ESL students' pre-writing strategy use but fail to detect significant effects on the students' writing quantity and writing quality; however, a trend of improvement regarding the writing quality variables was detected among the strategy-trained students. Furthermore, the qualitative analysis revealed some similarities and differences of less experienced and experienced writers' writing processes and strategies. Overall, the findings suggest the complex interplay among the factors influencing student writing development including writing strategy use, writing processes, writing tasks, task conditions, their past writing experience, and their language proficiency.

The purpose of this diploma thesis is to analyse time management methods and their application in secondary education. The theoretical part of the thesis focuses on different time management methods, which are available to teachers and pupils in secondary education. Special attention is paid to the representation of this topic in the Framework Educational Programs (FEPs) for basic education, Gymnasium and secondary vocational education. The practical part deals with how teachers and pupils use these methods. Teachers are also asked how they pass their knowledge of time management to their pupils. The research is realized in the form of semi- structured interviews with teachers and psychologists. The interviews showed that time management is not systematically taught in schools. The result of this diploma thesis is a description of useful methods and recommendations for their practical application in the educational process.

Au cours des dernières années, la communauté robotique s'est largement intéressée au domaine de l'interaction homme-robot (HRI). Un des aspects de ce domaine est de faire agir les robots en présence de l'homme, tout en respectant sa sécurité ainsi que son confort. Pour atteindre cet objectif, un robot doit planifier ses actions tout en prenant explicitement en compte les humains afin d'adapter le plan à leurs positions, leurs capacités et leurs préférences. La première partie de cette thèse concerne les transferts d'objets entre humains et robots : où, quand et comment les effectuer? Dépendant des préférences de l'Homme, il est parfois préférable, ou pas, partager l'effort du transfert d'objet entre lui et le robot, mais encore, à certains moments, un seul transfert d'objet n'est pas suffisant pour atteindre l'objectif (amener l'objet à un agent cible), le robot doit alors planifier une séquence de transfert d'objet entre plusieurs agents afin d'arriver à ses fins. Quel que soit le cas, pendant le transfert d'objet, un certain nombre de signaux doivent être échangés par les deux protagonistes afin de réussir l'action. Un des signaux les plus utilisés est le regard. Lorsque le donneur tend le bras afin de transférer l'objet, il doit regarder successivement le receveur puis l'objet afin de faciliter le transfert. Le transfert d'objet peut être considéré comme une action de base dans un plan plus vaste, nous amenant à la seconde partie de cette thèse qui présente une formalization de ce type d'actions de base" et d'actions plus complexes utilisant des conditions, des espaces de recherche et des contraintes. Cette partie rend aussi compte du framework et des différents algorithmes utilisés pour résoudre et calculer ces actions en fonction de leur description. La dernière partie de la thèse montre comment ce framework peut s'adapter à un planificateur de plus haut niveau (un planificateur de tâches par exemple) et une méthode pour combiner la planification symbolique et géométrique. Le planificateur de tâches utilise des appels à des fonctions externes lui permettant de vérifier la faisabilité de la tâche courante, et en cas de succès, de récupérer l'état du monde fourni par le raisonneur géométrique et de l'utilisé afin de poursuivre la planification. Cette partie montre également différentes extensions de cette algorithme, tels que les \validation géométriques" où nous testons l'infaisabilité de plusieurs actions à la fois ou \les contraintes" où l'ajout de contraintes au niveau symbolique peut dirigée la recherche géométrique ou encore \recherche dirigé par coût" où le planificateur symbolique utilise les informations fournies par la partie géométrique afin d'éviter le calcul de plans moins intéressants. / In the last few years, the Human robot interaction (HRI) field has been in the spotlight of the robotics community. One aspect of this field is making robots act in the presence of humans, while keeping them safe and comfortable. In order to achieve this, a robot needs to plan its actions while explicitly taking into account the humans and adapt its plans to their whereabouts, capacities and preferences. The first part of this thesis is about human-robot handover: where, when and how to perform them? Depending on the human preferences, it may be better, or not, to share the handover effort between him and the robot, while in other cases, a unique handover might not be enough to achieve the goal (bringing the object to a target agent) and a sequence of handovers might be needed. In any case, during the handover, a number of cues should be used by both protagonists involved in one handover. One of the most used cue is the gaze. When the giver reaches out with his arm, he should look at the object, and when the motion is finished, he should look at the receiver's face to facilitate the transfer. The handover can be considered as a basic action in a bigger plan. The second part of this thesis reports about a formalization of these kind of basic actions" and more complex ones by the use of conditions, search spaces and restraints. It also reports about a framework and different algorithms used to solve and compute these actions based on their description. The last part of the thesis shows how the previously cited framework can fit in with a higher level planner (such as a task planner) and a method to combine a symbolic and geometric planner. The task planner uses external calls to the geometric planner to assess the feasibility of the current task, and in case of success, retrieve the state of the world provided by the geometric reasoner and use it to continue the planning. This part also shows different extensions enabling a faster search. Some of these extensions are \Geometric checks" where we test the infeasibility of multiple actions at once, \constraints" where adding constraints at the symbolic level can drive the geometric search, and \cost driven search" where the symbolic planner uses information form the geometric one to prune out over costly plans.

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In an attempt to investigate the impact of planning on second language (L2) oral production, an experimental study that contrasted the effects of two types of pre-task planning (strategic planning vs. rehearsal) on the L2 oral task performance of 64 Japanese university EFL learners under different modality (aural vs. written) and language (L1 vs. L2) conditions of pre-task input was conducted. The main aim was to determine whether strategic planning (i.e., silent preparation) and rehearsal (i.e., active practice) before L2 oral tasks differentially impact performance in terms of fluency, complexity, and accuracy. An additional aim was to examine the effects on performance of providing pre-task input to assist planning. Furthermore, I elicited the learners’ perceptions of the value of the pre-task input toward assisting their oral task performance via 5-point Likert scale post-task questionnaires. No difference was found between strategic planning and rehearsal in their effects on L2 oral task performance regarding fluency, complexity, or accuracy. This result suggests that, when it comes to pre-task planning, L2 teachers can generally have their learners engage in either strategic planning or rehearsal without differentially impacting their task performance. Concerning the provision of pre-task input, the L1 and L2 input induced commensurate levels of fluency and complexity. However, the L2 input led to significantly greater accuracy of oral production than did the L1 input. This finding is important as it suggests that L2 learners can possibly acquire something from the input provided to them in the course of pre-task planning. Moreover, the post-task questionnaire results corroborated this finding as the participants indicated that the L2 input significantly enhanced their accuracy and also helped them use a wider range of vocabulary during the tasks. Thus, if the aim of a teaching or testing situation is oriented toward fluency, the results indicate that it makes no difference whether pre-task input is in learners’ L1 or L2. In contrast, if the aim is oriented toward accuracy, then teachers and testers should provide L2 input in order to facilitate optimal performance. / Language Arts