On the Minimal Revision Problem of Specification Automata

As robots are being integrated into our daily lives, it becomes necessary to provide guarantees on the safe and provably correct operation. Such guarantees can be provided using automata theoretic task and mission planning where the requirements are expressed as temporal logic specifications. However, in real-life scenarios, it is to be expected that not all user task requirements can be realized by the robot. In such cases, the robot must provide feedback to the user on why it cannot accomplish a given task. Moreover, the robot should indicate what tasks it can accomplish which are as "close" as possible to the initial user intent. This paper establishes that the latter problem, which is referred to as the minimal specification revision problem, is NP complete. A heuristic algorithm is presented that can compute good approximations to the Minimal Revision Problem (MRP) in polynomial time. The experimental study of the algorithm demonstrates that in most problem instances the heuristic algorithm actually returns the optimal solution. Finally, some cases where the algorithm does not return the optimal solution are presented.Comment: 23 pages, 16 figures, 2 tables, International Joural of Robotics Research 2014 Major Revision (submitted

Activation des processus rédactionnels et qualité des textes

The relations between the processes of planning and revision and quality of texts produced by adults are explored by referring to experiments using various methods (guidance of the activity, drafts analyses, cognitive effort tasks) and starting from three questions. The first one relates to the impact of these two processes on text quality: Is it necessary to plan and to revise in order to write good texts? The second question relates to the implementation of these processes: how to help writers in better exploiting them during writing. The third question relates to the writers adjustment "to situate" their activity: Do they have ready-made solutions to produce certain types of texts and not others? If so, do they engage differently in the task? How do they coordinate these processes which allow a control by anticipation (planning) and a posteriori (revision). The main results show that (1) certain ways of planning and of revising are more effective than others and (2) depending on the writing context, writers must carry out tradeoffs between the implementation of the processes and their respective costs: They can use either planning or revision to reach comparable results. Finally, it remains difficult (1) to specify the linguistic dimensions that must be taken into account for assessing text quality and (2) to develop objective indexes which better account for the trade-offs between the cost of planning and of revision and the quality of the texts

LLaMA Rider: Spurring Large Language Models to Explore the Open World

Recently, various studies have leveraged Large Language Models (LLMs) to help decision-making and planning in environments, and try to align the LLMs' knowledge with the world conditions. Nonetheless, the capacity of LLMs to continuously acquire environmental knowledge and adapt in an open world remains uncertain. In this paper, we propose an approach to spur LLMs to explore the open world, gather experiences, and learn to improve their task-solving capabilities. In this approach, a multi-round feedback-revision mechanism is utilized to encourage LLMs to actively select appropriate revision actions guided by feedback information from the environment. This facilitates exploration and enhances the model's performance. Besides, we integrate sub-task relabeling to assist LLMs in maintaining consistency in sub-task planning and help the model learn the combinatorial nature between tasks, enabling it to complete a wider range of tasks through training based on the acquired exploration experiences. By evaluation in Minecraft, an open-ended sandbox world, we demonstrate that our approach LLaMA-Rider enhances the efficiency of the LLM in exploring the environment, and effectively improves the LLM's ability to accomplish more tasks through fine-tuning with merely 1.3k instances of collected data, showing minimal training costs compared to the baseline using reinforcement learning.Comment: 18 page

Autoplan: A self-processing network model for an extended blocks world planning environment

Self-processing network models (neural/connectionist models, marker passing/message passing networks, etc.) are currently undergoing intense investigation for a variety of information processing applications. These models are potentially very powerful in that they support a large amount of explicit parallel processing, and they cleanly integrate high level and low level information processing. However they are currently limited by a lack of understanding of how to apply them effectively in many application areas. The formulation of self-processing network methods for dynamic, reactive planning is studied. The long-term goal is to formulate robust, computationally effective information processing methods for the distributed control of semiautonomous exploration systems, e.g., the Mars Rover. The current research effort is focusing on hierarchical plan generation, execution and revision through local operations in an extended blocks world environment. This scenario involves many challenging features that would be encountered in a real planning and control environment: multiple simultaneous goals, parallel as well as sequential action execution, action sequencing determined not only by goals and their interactions but also by limited resources (e.g., three tasks, two acting agents), need to interpret unanticipated events and react appropriately through replanning, etc

(Un)Complicating Planning and Revising: Metacognition and Problem-Based Tutoring

Why do clients struggle with creating rhetorical plans and globally revising their texts, and how can peer tutors help clients cultivate effective planning and revision practices? Problems with planning and revising differ depending upon the student and the task. Nevertheless, many clients may struggle because they don’t view writing as a problem-solving process that involves addressing a particular audience, selecting and narrowing not only a “topic” but a thesis and support, establishing a purpose for the text, and creating a persona. Instead, clients come to writing with “ideas” for what they want to write about and begin producing text as soon as they feel they have “something to say.” Because clients have paid scant attention to audience, purpose, or persona, as their resulting products show, they have no starting point from which to review how or if their texts have successfully addressed an audience, achieved a purpose, or created an ethos.University Writing Cente

Working Memory in Writing: Empirical Evidence From the Dual-Task Technique

The dual-task paradigm recently played a major role in understanding the role of working memory in writing. By reviewing recent findings in this field of research, this article highlights how the use of the dual-task technique allowed studying processing and short-term storage functions of working memory involved in writing. With respect to processing functions of working memory (namely, attentional and executive functions), studies investigated resources allocation, step-by-step management and parallel coordination of the writing processes. With respect to short-term storage in working memory, experiments mainly attempted to test Kellogg's (1996) proposals on the relationship between the writing processes and the slave systems of working memory. It is concluded that the dual-task technique revealed fruitful in understanding the relationship between writing and working memory

Media E-Learning Application Strategic PLADACYS: Planning, Design, and Action to Corporate Analysis-Based Android In the Strategic Management Course

Strategic Management, is a course that must be taken by all undergraduate students majoring in Management at the Faculty of Economics. And during this learning model that is applied face-to-face lecturers still often only use PPT media and provide tasks directly. The goal of the development of media e-learning Application Strategic PLADACYS (Planning, Design, and Action to Corporate Analysis-Based Android) in this strategic management course is to create and develop more innovative electronic learning media and provide more interactive learning media to students adjusting to the free learning curriculum.   Millennials are referring to technology. Learning tools developed in the form of e-learning media that can be installed on Android in the form of Strategic   Planning analysis (SPA) menu, Strategic design analysis  (SDA), Strategic action analysis (SAA) menus and menus in this application will contain a grouping of materials, tasks, and practices of strategic management lectures by following the symbol menu (SPA) Theory for planning, designing strategies with analytical tools.  (SDA) and looking for data to the company or industry as well as the practice of knowing the determinants of the company's success and analyzing (SAA). The development method carried out is the Borg &Gall development model [1] using waterfall grooves(waterfall)at the stage of development. The development stages begin with needs analysis, product planning, product development, trial/implementation (validation), revision, and report creation.  The product results in the form of Application Strategic PLADACYS (Planning, Design, and Action to Corporate Analysis-Based Android) as a learning medium in strategic management courses, and will be equipped with media application videos, as well as media usage instructions.

Drawing cartoon faces - a functional imaging study of the cognitive neuroscience of drawing

We report a functional imaging study of drawing cartoon faces. Normal, untrained participants were scanned while viewing simple black and white cartoon line-drawings of human faces, retaining them for a short memory interval, and then drawing them without vision of their hand or the paper. Specific encoding and retention of information about the faces was tested for by contrasting these two stages (with display of cartoon faces) against the exploration and retention of random dot stimuli. Drawing was contrasted between conditions in which only memory of a previously viewed face was available versus a condition in which both memory and simultaneous viewing of the cartoon was possible, and versus drawing of a new, previously unseen, face. We show that the encoding of cartoon faces powerfully activates the face sensitive areas of the lateral occipital cortex and the fusiform gyrus, but there is no significant activation in these areas during the retention interval. Activity in both areas was also high when drawing the displayed cartoons. Drawing from memory activates areas in posterior parietal cortex and frontal areas. This activity is consistent with the encoding and retention of the spatial information about the face to be drawn as a visuo-motor action plan, either representing a series of targets for ocular fixation or as spatial targets for the drawing actio

An Architectural Approach to Ensuring Consistency in Hierarchical Execution

Hierarchical task decomposition is a method used in many agent systems to organize agent knowledge. This work shows how the combination of a hierarchy and persistent assertions of knowledge can lead to difficulty in maintaining logical consistency in asserted knowledge. We explore the problematic consequences of persistent assumptions in the reasoning process and introduce novel potential solutions. Having implemented one of the possible solutions, Dynamic Hierarchical Justification, its effectiveness is demonstrated with an empirical analysis